---
_id: '10022'
abstract:
- lang: eng
text: We consider finite-volume approximations of Fokker-Planck equations on bounded
convex domains in R^d and study the corresponding gradient flow structures. We
reprove the convergence of the discrete to continuous Fokker-Planck equation via
the method of Evolutionary Γ-convergence, i.e., we pass to the limit at the level
of the gradient flow structures, generalising the one-dimensional result obtained
by Disser and Liero. The proof is of variational nature and relies on a Mosco
convergence result for functionals in the discrete-to-continuum limit that is
of independent interest. Our results apply to arbitrary regular meshes, even though
the associated discrete transport distances may fail to converge to the Wasserstein
distance in this generality.
acknowledgement: This work is supported by the European Research Council (ERC) under
the European Union’s Horizon 2020 research and innovation programme (grant agreement
No 716117) and by the Austrian Science Fund (FWF), grants No F65 and W1245.
article_number: '2008.10962'
article_processing_charge: No
author:
- first_name: Dominik L
full_name: Forkert, Dominik L
id: 35C79D68-F248-11E8-B48F-1D18A9856A87
last_name: Forkert
- first_name: Jan
full_name: Maas, Jan
id: 4C5696CE-F248-11E8-B48F-1D18A9856A87
last_name: Maas
orcid: 0000-0002-0845-1338
- first_name: Lorenzo
full_name: Portinale, Lorenzo
id: 30AD2CBC-F248-11E8-B48F-1D18A9856A87
last_name: Portinale
citation:
ama: Forkert DL, Maas J, Portinale L. Evolutionary Γ-convergence of entropic gradient
flow structures for Fokker-Planck equations in multiple dimensions. arXiv.
apa: Forkert, D. L., Maas, J., & Portinale, L. (n.d.). Evolutionary Γ-convergence
of entropic gradient flow structures for Fokker-Planck equations in multiple dimensions.
arXiv.
chicago: Forkert, Dominik L, Jan Maas, and Lorenzo Portinale. “Evolutionary Γ-Convergence
of Entropic Gradient Flow Structures for Fokker-Planck Equations in Multiple Dimensions.”
ArXiv, n.d.
ieee: D. L. Forkert, J. Maas, and L. Portinale, “Evolutionary Γ-convergence of entropic
gradient flow structures for Fokker-Planck equations in multiple dimensions,”
arXiv. .
ista: Forkert DL, Maas J, Portinale L. Evolutionary Γ-convergence of entropic gradient
flow structures for Fokker-Planck equations in multiple dimensions. arXiv, 2008.10962.
mla: Forkert, Dominik L., et al. “Evolutionary Γ-Convergence of Entropic Gradient
Flow Structures for Fokker-Planck Equations in Multiple Dimensions.” ArXiv,
2008.10962.
short: D.L. Forkert, J. Maas, L. Portinale, ArXiv (n.d.).
date_created: 2021-09-17T10:57:27Z
date_published: 2020-08-25T00:00:00Z
date_updated: 2023-09-07T13:31:05Z
day: '25'
department:
- _id: JaMa
ec_funded: 1
external_id:
arxiv:
- '2008.10962'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2008.10962
month: '08'
oa: 1
oa_version: Preprint
page: '33'
project:
- _id: 256E75B8-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '716117'
name: Optimal Transport and Stochastic Dynamics
- _id: fc31cba2-9c52-11eb-aca3-ff467d239cd2
grant_number: F6504
name: Taming Complexity in Partial Differential Systems
publication: arXiv
publication_status: submitted
related_material:
record:
- id: '11739'
relation: later_version
status: public
- id: '10030'
relation: dissertation_contains
status: public
status: public
title: Evolutionary Γ-convergence of entropic gradient flow structures for Fokker-Planck
equations in multiple dimensions
type: preprint
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2020'
...
---
_id: '8724'
abstract:
- lang: eng
text: "We study the problem of learning from multiple untrusted data sources, a
scenario of increasing practical relevance given the recent emergence of crowdsourcing
and collaborative learning paradigms. Specifically, we analyze the situation in
which a learning system obtains datasets from multiple sources, some of which
might be biased or even adversarially perturbed. It is\r\nknown that in the single-source
case, an adversary with the power to corrupt a fixed fraction of the training
data can prevent PAC-learnability, that is, even in the limit of infinitely much
training data, no learning system can approach the optimal test error. In this
work we show that, surprisingly, the same is not true in the multi-source setting,
where the adversary can arbitrarily\r\ncorrupt a fixed fraction of the data sources.
Our main results are a generalization bound that provides finite-sample guarantees
for this learning setting, as well as corresponding lower bounds. Besides establishing
PAC-learnability our results also show that in a cooperative learning setting
sharing data with other parties has provable benefits, even if some\r\nparticipants
are malicious. "
acknowledged_ssus:
- _id: ScienComp
acknowledgement: Dan Alistarh is supported in part by the European Research Council
(ERC) under the European Union’s Horizon 2020 research and innovation programme
(grant agreement No 805223 ScaleML). This research was supported by the Scientific
Service Units (SSU) of IST Austria through resources provided by Scientific Computing
(SciComp).
article_processing_charge: No
author:
- first_name: Nikola H
full_name: Konstantinov, Nikola H
id: 4B9D76E4-F248-11E8-B48F-1D18A9856A87
last_name: Konstantinov
- first_name: Elias
full_name: Frantar, Elias
id: 09a8f98d-ec99-11ea-ae11-c063a7b7fe5f
last_name: Frantar
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
- first_name: Christoph
full_name: Lampert, Christoph
id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
last_name: Lampert
orcid: 0000-0001-8622-7887
citation:
ama: 'Konstantinov NH, Frantar E, Alistarh D-A, Lampert C. On the sample complexity
of adversarial multi-source PAC learning. In: Proceedings of the 37th International
Conference on Machine Learning. Vol 119. ML Research Press; 2020:5416-5425.'
apa: 'Konstantinov, N. H., Frantar, E., Alistarh, D.-A., & Lampert, C. (2020).
On the sample complexity of adversarial multi-source PAC learning. In Proceedings
of the 37th International Conference on Machine Learning (Vol. 119, pp. 5416–5425).
Online: ML Research Press.'
chicago: Konstantinov, Nikola H, Elias Frantar, Dan-Adrian Alistarh, and Christoph
Lampert. “On the Sample Complexity of Adversarial Multi-Source PAC Learning.”
In Proceedings of the 37th International Conference on Machine Learning,
119:5416–25. ML Research Press, 2020.
ieee: N. H. Konstantinov, E. Frantar, D.-A. Alistarh, and C. Lampert, “On the sample
complexity of adversarial multi-source PAC learning,” in Proceedings of the
37th International Conference on Machine Learning, Online, 2020, vol. 119,
pp. 5416–5425.
ista: 'Konstantinov NH, Frantar E, Alistarh D-A, Lampert C. 2020. On the sample
complexity of adversarial multi-source PAC learning. Proceedings of the 37th International
Conference on Machine Learning. ICML: International Conference on Machine Learning
vol. 119, 5416–5425.'
mla: Konstantinov, Nikola H., et al. “On the Sample Complexity of Adversarial Multi-Source
PAC Learning.” Proceedings of the 37th International Conference on Machine
Learning, vol. 119, ML Research Press, 2020, pp. 5416–25.
short: N.H. Konstantinov, E. Frantar, D.-A. Alistarh, C. Lampert, in:, Proceedings
of the 37th International Conference on Machine Learning, ML Research Press, 2020,
pp. 5416–5425.
conference:
end_date: 2020-07-18
location: Online
name: 'ICML: International Conference on Machine Learning'
start_date: 2020-07-12
date_created: 2020-11-05T15:25:58Z
date_published: 2020-07-12T00:00:00Z
date_updated: 2023-09-07T13:42:08Z
day: '12'
ddc:
- '000'
department:
- _id: DaAl
- _id: ChLa
ec_funded: 1
external_id:
arxiv:
- '2002.10384'
file:
- access_level: open_access
checksum: cc755d0054bc4b2be778ea7aa7884d2f
content_type: application/pdf
creator: dernst
date_created: 2021-02-15T09:00:01Z
date_updated: 2021-02-15T09:00:01Z
file_id: '9120'
file_name: 2020_PMLR_Konstantinov.pdf
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success: 1
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intvolume: ' 119'
language:
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month: '07'
oa: 1
oa_version: Published Version
page: 5416-5425
project:
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '805223'
name: Elastic Coordination for Scalable Machine Learning
publication: Proceedings of the 37th International Conference on Machine Learning
publication_identifier:
issn:
- 2640-3498
publication_status: published
publisher: ML Research Press
quality_controlled: '1'
related_material:
link:
- relation: supplementary_material
url: http://proceedings.mlr.press/v119/konstantinov20a/konstantinov20a-supp.pdf
record:
- id: '10799'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: On the sample complexity of adversarial multi-source PAC learning
type: conference
user_id: 3E5EF7F0-F248-11E8-B48F-1D18A9856A87
volume: 119
year: '2020'
...
---
_id: '8644'
abstract:
- lang: eng
text: Determining the phase diagram of systems consisting of smaller subsystems
'connected' via a tunable coupling is a challenging task relevant for a variety
of physical settings. A general question is whether new phases, not present in
the uncoupled limit, may arise. We use machine learning and a suitable quasidistance
between different points of the phase diagram to study layered spin models, in
which the spin variables constituting each of the uncoupled systems (to which
we refer as layers) are coupled to each other via an interlayer coupling. In such
systems, in general, composite order parameters involving spins of different layers
may emerge as a consequence of the interlayer coupling. We focus on the layered
Ising and Ashkin–Teller models as a paradigmatic case study, determining their
phase diagram via the application of a machine learning algorithm to the Monte
Carlo data. Remarkably our technique is able to correctly characterize all the
system phases also in the case of hidden order parameters, i.e. order parameters
whose expression in terms of the microscopic configurations would require additional
preprocessing of the data fed to the algorithm. We correctly retrieve the three
known phases of the Ashkin–Teller model with ferromagnetic couplings, including
the phase described by a composite order parameter. For the bilayer and trilayer
Ising models the phases we find are only the ferromagnetic and the paramagnetic
ones. Within the approach we introduce, owing to the construction of convolutional
neural networks, naturally suitable for layered image-like data with arbitrary
number of layers, no preprocessing of the Monte Carlo data is needed, also with
regard to its spatial structure. The physical meaning of our results is discussed
and compared with analytical data, where available. Yet, the method can be used
without any a priori knowledge of the phases one seeks to find and can be applied
to other models and structures.
acknowledgement: We thank Gesualdo Delfino, Michele Fabrizio, Piero Ferrarese, Robert
Konik, Christoph Lampert and Mikhail Lemeshko for stimulating discussions at various
stages of this work. WR has received funding from the EU Horizon 2020 program under
the Marie Skłodowska-Curie Grant Agreement No. 665385 and is a recipient of a DOC
Fellowship of the Austrian Academy of Sciences. GB acknowledges support from the
Austrian Science Fund (FWF), under project No. M2641-N27. ND acknowledges support
by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) via Collaborative
Research Center SFB 1225 (ISOQUANT)--project-id 273811115--and under Germany's Excellence
Strategy 'EXC-2181/1-390900948' (the Heidelberg STRUCTURES Excellence Cluster).
article_number: '093026'
article_processing_charge: No
article_type: original
author:
- first_name: Wojciech
full_name: Rzadkowski, Wojciech
id: 48C55298-F248-11E8-B48F-1D18A9856A87
last_name: Rzadkowski
orcid: 0000-0002-1106-4419
- first_name: N
full_name: Defenu, N
last_name: Defenu
- first_name: S
full_name: Chiacchiera, S
last_name: Chiacchiera
- first_name: A
full_name: Trombettoni, A
last_name: Trombettoni
- first_name: Giacomo
full_name: Bighin, Giacomo
id: 4CA96FD4-F248-11E8-B48F-1D18A9856A87
last_name: Bighin
orcid: 0000-0001-8823-9777
citation:
ama: Rzadkowski W, Defenu N, Chiacchiera S, Trombettoni A, Bighin G. Detecting composite
orders in layered models via machine learning. New Journal of Physics.
2020;22(9). doi:10.1088/1367-2630/abae44
apa: Rzadkowski, W., Defenu, N., Chiacchiera, S., Trombettoni, A., & Bighin,
G. (2020). Detecting composite orders in layered models via machine learning.
New Journal of Physics. IOP Publishing. https://doi.org/10.1088/1367-2630/abae44
chicago: Rzadkowski, Wojciech, N Defenu, S Chiacchiera, A Trombettoni, and Giacomo
Bighin. “Detecting Composite Orders in Layered Models via Machine Learning.” New
Journal of Physics. IOP Publishing, 2020. https://doi.org/10.1088/1367-2630/abae44.
ieee: W. Rzadkowski, N. Defenu, S. Chiacchiera, A. Trombettoni, and G. Bighin, “Detecting
composite orders in layered models via machine learning,” New Journal of Physics,
vol. 22, no. 9. IOP Publishing, 2020.
ista: Rzadkowski W, Defenu N, Chiacchiera S, Trombettoni A, Bighin G. 2020. Detecting
composite orders in layered models via machine learning. New Journal of Physics.
22(9), 093026.
mla: Rzadkowski, Wojciech, et al. “Detecting Composite Orders in Layered Models
via Machine Learning.” New Journal of Physics, vol. 22, no. 9, 093026,
IOP Publishing, 2020, doi:10.1088/1367-2630/abae44.
short: W. Rzadkowski, N. Defenu, S. Chiacchiera, A. Trombettoni, G. Bighin, New
Journal of Physics 22 (2020).
date_created: 2020-10-11T22:01:14Z
date_published: 2020-09-01T00:00:00Z
date_updated: 2023-09-07T13:44:16Z
day: '01'
ddc:
- '530'
department:
- _id: MiLe
doi: 10.1088/1367-2630/abae44
ec_funded: 1
external_id:
isi:
- '000573298000001'
file:
- access_level: open_access
checksum: c9238fff422e7a957c3a0d559f756b3a
content_type: application/pdf
creator: dernst
date_created: 2020-10-12T12:18:47Z
date_updated: 2020-10-12T12:18:47Z
file_id: '8650'
file_name: 2020_NewJournalPhysics_Rzdkowski.pdf
file_size: 2725143
relation: main_file
success: 1
file_date_updated: 2020-10-12T12:18:47Z
has_accepted_license: '1'
intvolume: ' 22'
isi: 1
issue: '9'
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
- _id: 05A235A0-7A3F-11EA-A408-12923DDC885E
grant_number: '25681'
name: Analytic and machine learning approaches to composite quantum impurities
- _id: 26986C82-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: M02641
name: A path-integral approach to composite impurities
publication: New Journal of Physics
publication_identifier:
issn:
- '13672630'
publication_status: published
publisher: IOP Publishing
quality_controlled: '1'
related_material:
record:
- id: '10759'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Detecting composite orders in layered models via machine learning
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 22
year: '2020'
...
---
_id: '8705'
abstract:
- lang: eng
text: We consider the quantum mechanical many-body problem of a single impurity
particle immersed in a weakly interacting Bose gas. The impurity interacts with
the bosons via a two-body potential. We study the Hamiltonian of this system in
the mean-field limit and rigorously show that, at low energies, the problem is
well described by the Fröhlich polaron model.
acknowledgement: Financial support through the European Research Council (ERC) under
the European Union’s Horizon 2020 research and innovation programme Grant agreement
No. 694227 (R.S.) and the Maria Skłodowska-Curie Grant agreement No. 665386 (K.M.)
is gratefully acknowledged. Funding Open access funding provided by Institute of
Science and Technology (IST Austria)
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: Krzysztof
full_name: Mysliwy, Krzysztof
id: 316457FC-F248-11E8-B48F-1D18A9856A87
last_name: Mysliwy
- first_name: Robert
full_name: Seiringer, Robert
id: 4AFD0470-F248-11E8-B48F-1D18A9856A87
last_name: Seiringer
orcid: 0000-0002-6781-0521
citation:
ama: Mysliwy K, Seiringer R. Microscopic derivation of the Fröhlich Hamiltonian
for the Bose polaron in the mean-field limit. Annales Henri Poincare. 2020;21(12):4003-4025.
doi:10.1007/s00023-020-00969-3
apa: Mysliwy, K., & Seiringer, R. (2020). Microscopic derivation of the Fröhlich
Hamiltonian for the Bose polaron in the mean-field limit. Annales Henri Poincare.
Springer Nature. https://doi.org/10.1007/s00023-020-00969-3
chicago: Mysliwy, Krzysztof, and Robert Seiringer. “Microscopic Derivation of the
Fröhlich Hamiltonian for the Bose Polaron in the Mean-Field Limit.” Annales
Henri Poincare. Springer Nature, 2020. https://doi.org/10.1007/s00023-020-00969-3.
ieee: K. Mysliwy and R. Seiringer, “Microscopic derivation of the Fröhlich Hamiltonian
for the Bose polaron in the mean-field limit,” Annales Henri Poincare,
vol. 21, no. 12. Springer Nature, pp. 4003–4025, 2020.
ista: Mysliwy K, Seiringer R. 2020. Microscopic derivation of the Fröhlich Hamiltonian
for the Bose polaron in the mean-field limit. Annales Henri Poincare. 21(12),
4003–4025.
mla: Mysliwy, Krzysztof, and Robert Seiringer. “Microscopic Derivation of the Fröhlich
Hamiltonian for the Bose Polaron in the Mean-Field Limit.” Annales Henri Poincare,
vol. 21, no. 12, Springer Nature, 2020, pp. 4003–25, doi:10.1007/s00023-020-00969-3.
short: K. Mysliwy, R. Seiringer, Annales Henri Poincare 21 (2020) 4003–4025.
date_created: 2020-10-25T23:01:19Z
date_published: 2020-12-01T00:00:00Z
date_updated: 2023-09-07T13:43:51Z
day: '01'
ddc:
- '530'
department:
- _id: RoSe
doi: 10.1007/s00023-020-00969-3
ec_funded: 1
external_id:
arxiv:
- '2003.12371'
isi:
- '000578111800002'
file:
- access_level: open_access
checksum: c12c9c1e6f08def245e42f3cb1d83827
content_type: application/pdf
creator: cziletti
date_created: 2020-10-27T12:49:04Z
date_updated: 2020-10-27T12:49:04Z
file_id: '8711'
file_name: 2020_Annales_Mysliwy.pdf
file_size: 469831
relation: main_file
success: 1
file_date_updated: 2020-10-27T12:49:04Z
has_accepted_license: '1'
intvolume: ' 21'
isi: 1
issue: '12'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
page: 4003-4025
project:
- _id: 25C6DC12-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '694227'
name: Analysis of quantum many-body systems
- _id: B67AFEDC-15C9-11EA-A837-991A96BB2854
name: IST Austria Open Access Fund
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication: Annales Henri Poincare
publication_identifier:
issn:
- 1424-0637
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
record:
- id: '11473'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Microscopic derivation of the Fröhlich Hamiltonian for the Bose polaron in
the mean-field limit
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 21
year: '2020'
...
---
_id: '10861'
abstract:
- lang: eng
text: We introduce in this paper AMT2.0, a tool for qualitative and quantitative
analysis of hybrid continuous and Boolean signals that combine numerical values
and discrete events. The evaluation of the signals is based on rich temporal specifications
expressed in extended signal temporal logic, which integrates timed regular expressions
within signal temporal logic. The tool features qualitative monitoring (property
satisfaction checking), trace diagnostics for explaining and justifying property
violations and specification-driven measurement of quantitative features of the
signal. We demonstrate the tool functionality on several running examples and
case studies, and evaluate its performance.
article_processing_charge: No
article_type: original
author:
- first_name: Dejan
full_name: Nickovic, Dejan
id: 41BCEE5C-F248-11E8-B48F-1D18A9856A87
last_name: Nickovic
- first_name: Olivier
full_name: Lebeltel, Olivier
last_name: Lebeltel
- first_name: Oded
full_name: Maler, Oded
last_name: Maler
- first_name: Thomas
full_name: Ferrere, Thomas
id: 40960E6E-F248-11E8-B48F-1D18A9856A87
last_name: Ferrere
orcid: 0000-0001-5199-3143
- first_name: Dogan
full_name: Ulus, Dogan
last_name: Ulus
citation:
ama: 'Nickovic D, Lebeltel O, Maler O, Ferrere T, Ulus D. AMT 2.0: Qualitative and
quantitative trace analysis with extended signal temporal logic. International
Journal on Software Tools for Technology Transfer. 2020;22(6):741-758. doi:10.1007/s10009-020-00582-z'
apa: 'Nickovic, D., Lebeltel, O., Maler, O., Ferrere, T., & Ulus, D. (2020).
AMT 2.0: Qualitative and quantitative trace analysis with extended signal temporal
logic. International Journal on Software Tools for Technology Transfer.
Springer Nature. https://doi.org/10.1007/s10009-020-00582-z'
chicago: 'Nickovic, Dejan, Olivier Lebeltel, Oded Maler, Thomas Ferrere, and Dogan
Ulus. “AMT 2.0: Qualitative and Quantitative Trace Analysis with Extended Signal
Temporal Logic.” International Journal on Software Tools for Technology Transfer.
Springer Nature, 2020. https://doi.org/10.1007/s10009-020-00582-z.'
ieee: 'D. Nickovic, O. Lebeltel, O. Maler, T. Ferrere, and D. Ulus, “AMT 2.0: Qualitative
and quantitative trace analysis with extended signal temporal logic,” International
Journal on Software Tools for Technology Transfer, vol. 22, no. 6. Springer
Nature, pp. 741–758, 2020.'
ista: 'Nickovic D, Lebeltel O, Maler O, Ferrere T, Ulus D. 2020. AMT 2.0: Qualitative
and quantitative trace analysis with extended signal temporal logic. International
Journal on Software Tools for Technology Transfer. 22(6), 741–758.'
mla: 'Nickovic, Dejan, et al. “AMT 2.0: Qualitative and Quantitative Trace Analysis
with Extended Signal Temporal Logic.” International Journal on Software Tools
for Technology Transfer, vol. 22, no. 6, Springer Nature, 2020, pp. 741–58,
doi:10.1007/s10009-020-00582-z.'
short: D. Nickovic, O. Lebeltel, O. Maler, T. Ferrere, D. Ulus, International Journal
on Software Tools for Technology Transfer 22 (2020) 741–758.
date_created: 2022-03-18T10:10:53Z
date_published: 2020-08-03T00:00:00Z
date_updated: 2023-09-08T11:52:02Z
day: '03'
department:
- _id: ToHe
doi: 10.1007/s10009-020-00582-z
external_id:
isi:
- '000555398600001'
intvolume: ' 22'
isi: 1
issue: '6'
keyword:
- Information Systems
- Software
language:
- iso: eng
month: '08'
oa_version: None
page: 741-758
publication: International Journal on Software Tools for Technology Transfer
publication_identifier:
eissn:
- 1433-2787
issn:
- 1433-2779
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
record:
- id: '299'
relation: earlier_version
status: public
scopus_import: '1'
status: public
title: 'AMT 2.0: Qualitative and quantitative trace analysis with extended signal
temporal logic'
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 22
year: '2020'
...
---
_id: '14125'
abstract:
- lang: eng
text: "Motivation: Recent technological advances have led to an increase in the
production and availability of single-cell data. The ability to integrate a set
of multi-technology measurements would allow the identification of biologically
or clinically meaningful observations through the unification of the perspectives
afforded by each technology. In most cases, however, profiling technologies consume
the used cells and thus pairwise correspondences between datasets are lost. Due
to the sheer size single-cell datasets can acquire, scalable algorithms that are
able to universally match single-cell measurements carried out in one cell to
its corresponding sibling in another technology are needed.\r\nResults: We propose
Single-Cell data Integration via Matching (SCIM), a scalable approach to recover
such correspondences in two or more technologies. SCIM assumes that cells share
a common (low-dimensional) underlying structure and that the underlying cell distribution
is approximately constant across technologies. It constructs a technology-invariant
latent space using an autoencoder framework with an adversarial objective. Multi-modal
datasets are integrated by pairing cells across technologies using a bipartite
matching scheme that operates on the low-dimensional latent representations. We
evaluate SCIM on a simulated cellular branching process and show that the cell-to-cell
matches derived by SCIM reflect the same pseudotime on the simulated dataset.
Moreover, we apply our method to two real-world scenarios, a melanoma tumor sample
and a human bone marrow sample, where we pair cells from a scRNA dataset to their
sibling cells in a CyTOF dataset achieving 90% and 78% cell-matching accuracy
for each one of the samples, respectively."
article_processing_charge: No
article_type: original
author:
- first_name: Stefan G
full_name: Stark, Stefan G
last_name: Stark
- first_name: Joanna
full_name: Ficek, Joanna
last_name: Ficek
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Ximena
full_name: Bonilla, Ximena
last_name: Bonilla
- first_name: Stéphane
full_name: Chevrier, Stéphane
last_name: Chevrier
- first_name: Franziska
full_name: Singer, Franziska
last_name: Singer
- first_name: Rudolf
full_name: Aebersold, Rudolf
last_name: Aebersold
- first_name: Faisal S
full_name: Al-Quaddoomi, Faisal S
last_name: Al-Quaddoomi
- first_name: Jonas
full_name: Albinus, Jonas
last_name: Albinus
- first_name: Ilaria
full_name: Alborelli, Ilaria
last_name: Alborelli
- first_name: Sonali
full_name: Andani, Sonali
last_name: Andani
- first_name: Per-Olof
full_name: Attinger, Per-Olof
last_name: Attinger
- first_name: Marina
full_name: Bacac, Marina
last_name: Bacac
- first_name: Daniel
full_name: Baumhoer, Daniel
last_name: Baumhoer
- first_name: Beatrice
full_name: Beck-Schimmer, Beatrice
last_name: Beck-Schimmer
- first_name: Niko
full_name: Beerenwinkel, Niko
last_name: Beerenwinkel
- first_name: Christian
full_name: Beisel, Christian
last_name: Beisel
- first_name: Lara
full_name: Bernasconi, Lara
last_name: Bernasconi
- first_name: Anne
full_name: Bertolini, Anne
last_name: Bertolini
- first_name: Bernd
full_name: Bodenmiller, Bernd
last_name: Bodenmiller
- first_name: Ximena
full_name: Bonilla, Ximena
last_name: Bonilla
- first_name: Ruben
full_name: Casanova, Ruben
last_name: Casanova
- first_name: Stéphane
full_name: Chevrier, Stéphane
last_name: Chevrier
- first_name: Natalia
full_name: Chicherova, Natalia
last_name: Chicherova
- first_name: Maya
full_name: D'Costa, Maya
last_name: D'Costa
- first_name: Esther
full_name: Danenberg, Esther
last_name: Danenberg
- first_name: Natalie
full_name: Davidson, Natalie
last_name: Davidson
- first_name: Monica-Andreea Dră
full_name: gan, Monica-Andreea Dră
last_name: gan
- first_name: Reinhard
full_name: Dummer, Reinhard
last_name: Dummer
- first_name: Stefanie
full_name: Engler, Stefanie
last_name: Engler
- first_name: Martin
full_name: Erkens, Martin
last_name: Erkens
- first_name: Katja
full_name: Eschbach, Katja
last_name: Eschbach
- first_name: Cinzia
full_name: Esposito, Cinzia
last_name: Esposito
- first_name: André
full_name: Fedier, André
last_name: Fedier
- first_name: Pedro
full_name: Ferreira, Pedro
last_name: Ferreira
- first_name: Joanna
full_name: Ficek, Joanna
last_name: Ficek
- first_name: Anja L
full_name: Frei, Anja L
last_name: Frei
- first_name: Bruno
full_name: Frey, Bruno
last_name: Frey
- first_name: Sandra
full_name: Goetze, Sandra
last_name: Goetze
- first_name: Linda
full_name: Grob, Linda
last_name: Grob
- first_name: Gabriele
full_name: Gut, Gabriele
last_name: Gut
- first_name: Detlef
full_name: Günther, Detlef
last_name: Günther
- first_name: Martina
full_name: Haberecker, Martina
last_name: Haberecker
- first_name: Pirmin
full_name: Haeuptle, Pirmin
last_name: Haeuptle
- first_name: Viola
full_name: Heinzelmann-Schwarz, Viola
last_name: Heinzelmann-Schwarz
- first_name: Sylvia
full_name: Herter, Sylvia
last_name: Herter
- first_name: Rene
full_name: Holtackers, Rene
last_name: Holtackers
- first_name: Tamara
full_name: Huesser, Tamara
last_name: Huesser
- first_name: Anja
full_name: Irmisch, Anja
last_name: Irmisch
- first_name: Francis
full_name: Jacob, Francis
last_name: Jacob
- first_name: Andrea
full_name: Jacobs, Andrea
last_name: Jacobs
- first_name: Tim M
full_name: Jaeger, Tim M
last_name: Jaeger
- first_name: Katharina
full_name: Jahn, Katharina
last_name: Jahn
- first_name: Alva R
full_name: James, Alva R
last_name: James
- first_name: Philip M
full_name: Jermann, Philip M
last_name: Jermann
- first_name: André
full_name: Kahles, André
last_name: Kahles
- first_name: Abdullah
full_name: Kahraman, Abdullah
last_name: Kahraman
- first_name: Viktor H
full_name: Koelzer, Viktor H
last_name: Koelzer
- first_name: Werner
full_name: Kuebler, Werner
last_name: Kuebler
- first_name: Jack
full_name: Kuipers, Jack
last_name: Kuipers
- first_name: Christian P
full_name: Kunze, Christian P
last_name: Kunze
- first_name: Christian
full_name: Kurzeder, Christian
last_name: Kurzeder
- first_name: Kjong-Van
full_name: Lehmann, Kjong-Van
last_name: Lehmann
- first_name: Mitchell
full_name: Levesque, Mitchell
last_name: Levesque
- first_name: Sebastian
full_name: Lugert, Sebastian
last_name: Lugert
- first_name: Gerd
full_name: Maass, Gerd
last_name: Maass
- first_name: Markus
full_name: Manz, Markus
last_name: Manz
- first_name: Philipp
full_name: Markolin, Philipp
last_name: Markolin
- first_name: Julien
full_name: Mena, Julien
last_name: Mena
- first_name: Ulrike
full_name: Menzel, Ulrike
last_name: Menzel
- first_name: Julian M
full_name: Metzler, Julian M
last_name: Metzler
- first_name: Nicola
full_name: Miglino, Nicola
last_name: Miglino
- first_name: Emanuela S
full_name: Milani, Emanuela S
last_name: Milani
- first_name: Holger
full_name: Moch, Holger
last_name: Moch
- first_name: Simone
full_name: Muenst, Simone
last_name: Muenst
- first_name: Riccardo
full_name: Murri, Riccardo
last_name: Murri
- first_name: Charlotte KY
full_name: Ng, Charlotte KY
last_name: Ng
- first_name: Stefan
full_name: Nicolet, Stefan
last_name: Nicolet
- first_name: Marta
full_name: Nowak, Marta
last_name: Nowak
- first_name: Patrick GA
full_name: Pedrioli, Patrick GA
last_name: Pedrioli
- first_name: Lucas
full_name: Pelkmans, Lucas
last_name: Pelkmans
- first_name: Salvatore
full_name: Piscuoglio, Salvatore
last_name: Piscuoglio
- first_name: Michael
full_name: Prummer, Michael
last_name: Prummer
- first_name: Mathilde
full_name: Ritter, Mathilde
last_name: Ritter
- first_name: Christian
full_name: Rommel, Christian
last_name: Rommel
- first_name: María L
full_name: Rosano-González, María L
last_name: Rosano-González
- first_name: Gunnar
full_name: Rätsch, Gunnar
last_name: Rätsch
- first_name: Natascha
full_name: Santacroce, Natascha
last_name: Santacroce
- first_name: Jacobo Sarabia del
full_name: Castillo, Jacobo Sarabia del
last_name: Castillo
- first_name: Ramona
full_name: Schlenker, Ramona
last_name: Schlenker
- first_name: Petra C
full_name: Schwalie, Petra C
last_name: Schwalie
- first_name: Severin
full_name: Schwan, Severin
last_name: Schwan
- first_name: Tobias
full_name: Schär, Tobias
last_name: Schär
- first_name: Gabriela
full_name: Senti, Gabriela
last_name: Senti
- first_name: Franziska
full_name: Singer, Franziska
last_name: Singer
- first_name: Sujana
full_name: Sivapatham, Sujana
last_name: Sivapatham
- first_name: Berend
full_name: Snijder, Berend
last_name: Snijder
- first_name: Bettina
full_name: Sobottka, Bettina
last_name: Sobottka
- first_name: Vipin T
full_name: Sreedharan, Vipin T
last_name: Sreedharan
- first_name: Stefan
full_name: Stark, Stefan
last_name: Stark
- first_name: Daniel J
full_name: Stekhoven, Daniel J
last_name: Stekhoven
- first_name: Alexandre PA
full_name: Theocharides, Alexandre PA
last_name: Theocharides
- first_name: Tinu M
full_name: Thomas, Tinu M
last_name: Thomas
- first_name: Markus
full_name: Tolnay, Markus
last_name: Tolnay
- first_name: Vinko
full_name: Tosevski, Vinko
last_name: Tosevski
- first_name: Nora C
full_name: Toussaint, Nora C
last_name: Toussaint
- first_name: Mustafa A
full_name: Tuncel, Mustafa A
last_name: Tuncel
- first_name: Marina
full_name: Tusup, Marina
last_name: Tusup
- first_name: Audrey Van
full_name: Drogen, Audrey Van
last_name: Drogen
- first_name: Marcus
full_name: Vetter, Marcus
last_name: Vetter
- first_name: Tatjana
full_name: Vlajnic, Tatjana
last_name: Vlajnic
- first_name: Sandra
full_name: Weber, Sandra
last_name: Weber
- first_name: Walter P
full_name: Weber, Walter P
last_name: Weber
- first_name: Rebekka
full_name: Wegmann, Rebekka
last_name: Wegmann
- first_name: Michael
full_name: Weller, Michael
last_name: Weller
- first_name: Fabian
full_name: Wendt, Fabian
last_name: Wendt
- first_name: Norbert
full_name: Wey, Norbert
last_name: Wey
- first_name: Andreas
full_name: Wicki, Andreas
last_name: Wicki
- first_name: Bernd
full_name: Wollscheid, Bernd
last_name: Wollscheid
- first_name: Shuqing
full_name: Yu, Shuqing
last_name: Yu
- first_name: Johanna
full_name: Ziegler, Johanna
last_name: Ziegler
- first_name: Marc
full_name: Zimmermann, Marc
last_name: Zimmermann
- first_name: Martin
full_name: Zoche, Martin
last_name: Zoche
- first_name: Gregor
full_name: Zuend, Gregor
last_name: Zuend
- first_name: Gunnar
full_name: Rätsch, Gunnar
last_name: Rätsch
- first_name: Kjong-Van
full_name: Lehmann, Kjong-Van
last_name: Lehmann
citation:
ama: 'Stark SG, Ficek J, Locatello F, et al. SCIM: Universal single-cell matching
with unpaired feature sets. Bioinformatics. 2020;36(Supplement_2):i919-i927.
doi:10.1093/bioinformatics/btaa843'
apa: 'Stark, S. G., Ficek, J., Locatello, F., Bonilla, X., Chevrier, S., Singer,
F., … Lehmann, K.-V. (2020). SCIM: Universal single-cell matching with unpaired
feature sets. Bioinformatics. Oxford University Press. https://doi.org/10.1093/bioinformatics/btaa843'
chicago: 'Stark, Stefan G, Joanna Ficek, Francesco Locatello, Ximena Bonilla, Stéphane
Chevrier, Franziska Singer, Rudolf Aebersold, et al. “SCIM: Universal Single-Cell
Matching with Unpaired Feature Sets.” Bioinformatics. Oxford University
Press, 2020. https://doi.org/10.1093/bioinformatics/btaa843.'
ieee: 'S. G. Stark et al., “SCIM: Universal single-cell matching with unpaired
feature sets,” Bioinformatics, vol. 36, no. Supplement_2. Oxford University
Press, pp. i919–i927, 2020.'
ista: 'Stark SG et al. 2020. SCIM: Universal single-cell matching with unpaired
feature sets. Bioinformatics. 36(Supplement_2), i919–i927.'
mla: 'Stark, Stefan G., et al. “SCIM: Universal Single-Cell Matching with Unpaired
Feature Sets.” Bioinformatics, vol. 36, no. Supplement_2, Oxford University
Press, 2020, pp. i919–27, doi:10.1093/bioinformatics/btaa843.'
short: S.G. Stark, J. Ficek, F. Locatello, X. Bonilla, S. Chevrier, F. Singer, R.
Aebersold, F.S. Al-Quaddoomi, J. Albinus, I. Alborelli, S. Andani, P.-O. Attinger,
M. Bacac, D. Baumhoer, B. Beck-Schimmer, N. Beerenwinkel, C. Beisel, L. Bernasconi,
A. Bertolini, B. Bodenmiller, X. Bonilla, R. Casanova, S. Chevrier, N. Chicherova,
M. D’Costa, E. Danenberg, N. Davidson, M.-A.D. gan, R. Dummer, S. Engler, M. Erkens,
K. Eschbach, C. Esposito, A. Fedier, P. Ferreira, J. Ficek, A.L. Frei, B. Frey,
S. Goetze, L. Grob, G. Gut, D. Günther, M. Haberecker, P. Haeuptle, V. Heinzelmann-Schwarz,
S. Herter, R. Holtackers, T. Huesser, A. Irmisch, F. Jacob, A. Jacobs, T.M. Jaeger,
K. Jahn, A.R. James, P.M. Jermann, A. Kahles, A. Kahraman, V.H. Koelzer, W. Kuebler,
J. Kuipers, C.P. Kunze, C. Kurzeder, K.-V. Lehmann, M. Levesque, S. Lugert, G.
Maass, M. Manz, P. Markolin, J. Mena, U. Menzel, J.M. Metzler, N. Miglino, E.S.
Milani, H. Moch, S. Muenst, R. Murri, C.K. Ng, S. Nicolet, M. Nowak, P.G. Pedrioli,
L. Pelkmans, S. Piscuoglio, M. Prummer, M. Ritter, C. Rommel, M.L. Rosano-González,
G. Rätsch, N. Santacroce, J.S. del Castillo, R. Schlenker, P.C. Schwalie, S. Schwan,
T. Schär, G. Senti, F. Singer, S. Sivapatham, B. Snijder, B. Sobottka, V.T. Sreedharan,
S. Stark, D.J. Stekhoven, A.P. Theocharides, T.M. Thomas, M. Tolnay, V. Tosevski,
N.C. Toussaint, M.A. Tuncel, M. Tusup, A.V. Drogen, M. Vetter, T. Vlajnic, S.
Weber, W.P. Weber, R. Wegmann, M. Weller, F. Wendt, N. Wey, A. Wicki, B. Wollscheid,
S. Yu, J. Ziegler, M. Zimmermann, M. Zoche, G. Zuend, G. Rätsch, K.-V. Lehmann,
Bioinformatics 36 (2020) i919–i927.
date_created: 2023-08-21T12:28:20Z
date_published: 2020-12-01T00:00:00Z
date_updated: 2023-09-11T10:21:00Z
day: '01'
department:
- _id: FrLo
doi: 10.1093/bioinformatics/btaa843
extern: '1'
external_id:
pmid:
- '33381818'
intvolume: ' 36'
issue: Supplement_2
keyword:
- Computational Mathematics
- Computational Theory and Mathematics
- Computer Science Applications
- Molecular Biology
- Biochemistry
- Statistics and Probability
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1093/bioinformatics/btaa843
month: '12'
oa: 1
oa_version: Published Version
page: i919-i927
pmid: 1
publication: Bioinformatics
publication_identifier:
eissn:
- 1367-4811
publication_status: published
publisher: Oxford University Press
quality_controlled: '1'
related_material:
link:
- relation: software
url: https://github.com/ratschlab/scim
scopus_import: '1'
status: public
title: 'SCIM: Universal single-cell matching with unpaired feature sets'
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 36
year: '2020'
...
---
_id: '14186'
abstract:
- lang: eng
text: "The goal of the unsupervised learning of disentangled representations is
to\r\nseparate the independent explanatory factors of variation in the data without\r\naccess
to supervision. In this paper, we summarize the results of Locatello et\r\nal.,
2019, and focus on their implications for practitioners. We discuss the\r\ntheoretical
result showing that the unsupervised learning of disentangled\r\nrepresentations
is fundamentally impossible without inductive biases and the\r\npractical challenges
it entails. Finally, we comment on our experimental\r\nfindings, highlighting
the limitations of state-of-the-art approaches and\r\ndirections for future research."
article_processing_charge: No
author:
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Stefan
full_name: Bauer, Stefan
last_name: Bauer
- first_name: Mario
full_name: Lucic, Mario
last_name: Lucic
- first_name: Gunnar
full_name: Rätsch, Gunnar
last_name: Rätsch
- first_name: Sylvain
full_name: Gelly, Sylvain
last_name: Gelly
- first_name: Bernhard
full_name: Schölkopf, Bernhard
last_name: Schölkopf
- first_name: Olivier
full_name: Bachem, Olivier
last_name: Bachem
citation:
ama: 'Locatello F, Bauer S, Lucic M, et al. A commentary on the unsupervised learning
of disentangled representations. In: The 34th AAAI Conference on Artificial
Intelligence. Vol 34. Association for the Advancement of Artificial Intelligence;
2020:13681-13684. doi:10.1609/aaai.v34i09.7120'
apa: 'Locatello, F., Bauer, S., Lucic, M., Rätsch, G., Gelly, S., Schölkopf, B.,
& Bachem, O. (2020). A commentary on the unsupervised learning of disentangled
representations. In The 34th AAAI Conference on Artificial Intelligence
(Vol. 34, pp. 13681–13684). New York, NY, United States: Association for the Advancement
of Artificial Intelligence. https://doi.org/10.1609/aaai.v34i09.7120'
chicago: Locatello, Francesco, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain
Gelly, Bernhard Schölkopf, and Olivier Bachem. “A Commentary on the Unsupervised
Learning of Disentangled Representations.” In The 34th AAAI Conference on Artificial
Intelligence, 34:13681–84. Association for the Advancement of Artificial Intelligence,
2020. https://doi.org/10.1609/aaai.v34i09.7120.
ieee: F. Locatello et al., “A commentary on the unsupervised learning of
disentangled representations,” in The 34th AAAI Conference on Artificial Intelligence,
New York, NY, United States, 2020, vol. 34, no. 9, pp. 13681–13684.
ista: 'Locatello F, Bauer S, Lucic M, Rätsch G, Gelly S, Schölkopf B, Bachem O.
2020. A commentary on the unsupervised learning of disentangled representations.
The 34th AAAI Conference on Artificial Intelligence. AAAI: Conference on Artificial
Intelligence vol. 34, 13681–13684.'
mla: Locatello, Francesco, et al. “A Commentary on the Unsupervised Learning of
Disentangled Representations.” The 34th AAAI Conference on Artificial Intelligence,
vol. 34, no. 9, Association for the Advancement of Artificial Intelligence, 2020,
pp. 13681–84, doi:10.1609/aaai.v34i09.7120.
short: F. Locatello, S. Bauer, M. Lucic, G. Rätsch, S. Gelly, B. Schölkopf, O. Bachem,
in:, The 34th AAAI Conference on Artificial Intelligence, Association for the
Advancement of Artificial Intelligence, 2020, pp. 13681–13684.
conference:
end_date: 2020-02-12
location: New York, NY, United States
name: 'AAAI: Conference on Artificial Intelligence'
start_date: 2020-02-07
date_created: 2023-08-22T14:07:26Z
date_published: 2020-07-28T00:00:00Z
date_updated: 2023-09-12T07:44:48Z
day: '28'
department:
- _id: FrLo
doi: 10.1609/aaai.v34i09.7120
extern: '1'
external_id:
arxiv:
- '2007.14184'
intvolume: ' 34'
issue: '9'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2007.14184
month: '07'
oa: 1
oa_version: Preprint
page: 13681-13684
publication: The 34th AAAI Conference on Artificial Intelligence
publication_identifier:
eissn:
- 2374-3468
isbn:
- '9781577358350'
publication_status: published
publisher: Association for the Advancement of Artificial Intelligence
quality_controlled: '1'
scopus_import: '1'
status: public
title: A commentary on the unsupervised learning of disentangled representations
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 34
year: '2020'
...
---
_id: '14188'
abstract:
- lang: eng
text: "Intelligent agents should be able to learn useful representations by\r\nobserving
changes in their environment. We model such observations as pairs of\r\nnon-i.i.d.
images sharing at least one of the underlying factors of variation.\r\nFirst,
we theoretically show that only knowing how many factors have changed,\r\nbut
not which ones, is sufficient to learn disentangled representations.\r\nSecond,
we provide practical algorithms that learn disentangled representations\r\nfrom
pairs of images without requiring annotation of groups, individual\r\nfactors,
or the number of factors that have changed. Third, we perform a\r\nlarge-scale
empirical study and show that such pairs of observations are\r\nsufficient to
reliably learn disentangled representations on several benchmark\r\ndata sets.
Finally, we evaluate our learned representations and find that they\r\nare simultaneously
useful on a diverse suite of tasks, including generalization\r\nunder covariate
shifts, fairness, and abstract reasoning. Overall, our results\r\ndemonstrate
that weak supervision enables learning of useful disentangled\r\nrepresentations
in realistic scenarios."
alternative_title:
- PMLR
article_processing_charge: No
author:
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Ben
full_name: Poole, Ben
last_name: Poole
- first_name: Gunnar
full_name: Rätsch, Gunnar
last_name: Rätsch
- first_name: Bernhard
full_name: Schölkopf, Bernhard
last_name: Schölkopf
- first_name: Olivier
full_name: Bachem, Olivier
last_name: Bachem
- first_name: Michael
full_name: Tschannen, Michael
last_name: Tschannen
citation:
ama: 'Locatello F, Poole B, Rätsch G, Schölkopf B, Bachem O, Tschannen M. Weakly-supervised
disentanglement without compromises. In: Proceedings of the 37th International
Conference on Machine Learning. Vol 119. ; 2020:6348–6359.'
apa: Locatello, F., Poole, B., Rätsch, G., Schölkopf, B., Bachem, O., & Tschannen,
M. (2020). Weakly-supervised disentanglement without compromises. In Proceedings
of the 37th International Conference on Machine Learning (Vol. 119, pp. 6348–6359).
Virtual.
chicago: Locatello, Francesco, Ben Poole, Gunnar Rätsch, Bernhard Schölkopf, Olivier
Bachem, and Michael Tschannen. “Weakly-Supervised Disentanglement without Compromises.”
In Proceedings of the 37th International Conference on Machine Learning,
119:6348–6359, 2020.
ieee: F. Locatello, B. Poole, G. Rätsch, B. Schölkopf, O. Bachem, and M. Tschannen,
“Weakly-supervised disentanglement without compromises,” in Proceedings of
the 37th International Conference on Machine Learning, Virtual, 2020, vol.
119, pp. 6348–6359.
ista: Locatello F, Poole B, Rätsch G, Schölkopf B, Bachem O, Tschannen M. 2020.
Weakly-supervised disentanglement without compromises. Proceedings of the 37th
International Conference on Machine Learning. International Conference on Machine
Learning, PMLR, vol. 119, 6348–6359.
mla: Locatello, Francesco, et al. “Weakly-Supervised Disentanglement without Compromises.”
Proceedings of the 37th International Conference on Machine Learning, vol.
119, 2020, pp. 6348–6359.
short: F. Locatello, B. Poole, G. Rätsch, B. Schölkopf, O. Bachem, M. Tschannen,
in:, Proceedings of the 37th International Conference on Machine Learning, 2020,
pp. 6348–6359.
conference:
end_date: 2020-07-18
location: Virtual
name: International Conference on Machine Learning
start_date: 2020-07-13
date_created: 2023-08-22T14:08:14Z
date_published: 2020-07-07T00:00:00Z
date_updated: 2023-09-12T07:59:29Z
day: '07'
department:
- _id: FrLo
extern: '1'
external_id:
arxiv:
- '2002.02886'
intvolume: ' 119'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2002.02886
month: '07'
oa: 1
oa_version: Preprint
page: 6348–6359
publication: Proceedings of the 37th International Conference on Machine Learning
publication_status: published
quality_controlled: '1'
scopus_import: '1'
status: public
title: Weakly-supervised disentanglement without compromises
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 119
year: '2020'
...
---
_id: '14187'
abstract:
- lang: eng
text: "We propose a novel Stochastic Frank-Wolfe (a.k.a. conditional gradient)\r\nalgorithm
for constrained smooth finite-sum minimization with a generalized\r\nlinear prediction/structure.
This class of problems includes empirical risk\r\nminimization with sparse, low-rank,
or other structured constraints. The\r\nproposed method is simple to implement,
does not require step-size tuning, and\r\nhas a constant per-iteration cost that
is independent of the dataset size.\r\nFurthermore, as a byproduct of the method
we obtain a stochastic estimator of\r\nthe Frank-Wolfe gap that can be used as
a stopping criterion. Depending on the\r\nsetting, the proposed method matches
or improves on the best computational\r\nguarantees for Stochastic Frank-Wolfe
algorithms. Benchmarks on several\r\ndatasets highlight different regimes in which
the proposed method exhibits a\r\nfaster empirical convergence than related methods.
Finally, we provide an\r\nimplementation of all considered methods in an open-source
package."
alternative_title:
- PMLR
article_processing_charge: No
author:
- first_name: Geoffrey
full_name: Négiar, Geoffrey
last_name: Négiar
- first_name: Gideon
full_name: Dresdner, Gideon
last_name: Dresdner
- first_name: Alicia
full_name: Tsai, Alicia
last_name: Tsai
- first_name: Laurent El
full_name: Ghaoui, Laurent El
last_name: Ghaoui
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Robert M.
full_name: Freund, Robert M.
last_name: Freund
- first_name: Fabian
full_name: Pedregosa, Fabian
last_name: Pedregosa
citation:
ama: 'Négiar G, Dresdner G, Tsai A, et al. Stochastic Frank-Wolfe for constrained
finite-sum minimization. In: Proceedings of the 37th International Conference
on Machine Learning. Vol 119. ; 2020:7253-7262.'
apa: Négiar, G., Dresdner, G., Tsai, A., Ghaoui, L. E., Locatello, F., Freund, R.
M., & Pedregosa, F. (2020). Stochastic Frank-Wolfe for constrained finite-sum
minimization. In Proceedings of the 37th International Conference on Machine
Learning (Vol. 119, pp. 7253–7262). Virtual.
chicago: Négiar, Geoffrey, Gideon Dresdner, Alicia Tsai, Laurent El Ghaoui, Francesco
Locatello, Robert M. Freund, and Fabian Pedregosa. “Stochastic Frank-Wolfe for
Constrained Finite-Sum Minimization.” In Proceedings of the 37th International
Conference on Machine Learning, 119:7253–62, 2020.
ieee: G. Négiar et al., “Stochastic Frank-Wolfe for constrained finite-sum
minimization,” in Proceedings of the 37th International Conference on Machine
Learning, Virtual, 2020, vol. 119, pp. 7253–7262.
ista: Négiar G, Dresdner G, Tsai A, Ghaoui LE, Locatello F, Freund RM, Pedregosa
F. 2020. Stochastic Frank-Wolfe for constrained finite-sum minimization. Proceedings
of the 37th International Conference on Machine Learning. International Conference
on Machine Learning, PMLR, vol. 119, 7253–7262.
mla: Négiar, Geoffrey, et al. “Stochastic Frank-Wolfe for Constrained Finite-Sum
Minimization.” Proceedings of the 37th International Conference on Machine
Learning, vol. 119, 2020, pp. 7253–62.
short: G. Négiar, G. Dresdner, A. Tsai, L.E. Ghaoui, F. Locatello, R.M. Freund,
F. Pedregosa, in:, Proceedings of the 37th International Conference on Machine
Learning, 2020, pp. 7253–7262.
conference:
end_date: 2020-07-18
location: Virtual
name: International Conference on Machine Learning
start_date: 2020-07-13
date_created: 2023-08-22T14:07:52Z
date_published: 2020-07-27T00:00:00Z
date_updated: 2023-09-12T08:03:40Z
day: '27'
department:
- _id: FrLo
extern: '1'
external_id:
arxiv:
- '2002.11860'
intvolume: ' 119'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2002.11860
month: '07'
oa: 1
oa_version: Preprint
page: 7253-7262
publication: Proceedings of the 37th International Conference on Machine Learning
publication_status: published
quality_controlled: '1'
status: public
title: Stochastic Frank-Wolfe for constrained finite-sum minimization
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 119
year: '2020'
...
---
_id: '14195'
abstract:
- lang: eng
text: "The idea behind the unsupervised learning of disentangled representations
is that real-world data is generated by a few explanatory factors of variation
which can be recovered by unsupervised learning algorithms. In this paper, we
provide a sober look at recent progress in the field and challenge some common
assumptions. We first theoretically show that the unsupervised learning of disentangled
representations is fundamentally impossible without inductive biases on both the
models and the data. Then, we train over 14000\r\n models covering most prominent
methods and evaluation metrics in a reproducible large-scale experimental study
on eight data sets. We observe that while the different methods successfully enforce
properties “encouraged” by the corresponding losses, well-disentangled models
seemingly cannot be identified without supervision. Furthermore, different evaluation
metrics do not always agree on what should be considered “disentangled” and exhibit
systematic differences in the estimation. Finally, increased disentanglement does
not seem to necessarily lead to a decreased sample complexity of learning for
downstream tasks. Our results suggest that future work on disentanglement learning
should be explicit about the role of inductive biases and (implicit) supervision,
investigate concrete benefits of enforcing disentanglement of the learned representations,
and consider a reproducible experimental setup covering several data sets."
article_number: '209'
article_processing_charge: No
article_type: original
author:
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Stefan
full_name: Bauer, Stefan
last_name: Bauer
- first_name: Mario
full_name: Lucic, Mario
last_name: Lucic
- first_name: Gunnar
full_name: Rätsch, Gunnar
last_name: Rätsch
- first_name: Sylvain
full_name: Gelly, Sylvain
last_name: Gelly
- first_name: Bernhard
full_name: Schölkopf, Bernhard
last_name: Schölkopf
- first_name: Olivier
full_name: Bachem, Olivier
last_name: Bachem
citation:
ama: Locatello F, Bauer S, Lucic M, et al. A sober look at the unsupervised learning
of disentangled representations and their evaluation. Journal of Machine Learning
Research. 2020;21.
apa: Locatello, F., Bauer, S., Lucic, M., Rätsch, G., Gelly, S., Schölkopf, B.,
& Bachem, O. (2020). A sober look at the unsupervised learning of disentangled
representations and their evaluation. Journal of Machine Learning Research.
MIT Press.
chicago: Locatello, Francesco, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain
Gelly, Bernhard Schölkopf, and Olivier Bachem. “A Sober Look at the Unsupervised
Learning of Disentangled Representations and Their Evaluation.” Journal of
Machine Learning Research. MIT Press, 2020.
ieee: F. Locatello et al., “A sober look at the unsupervised learning of
disentangled representations and their evaluation,” Journal of Machine Learning
Research, vol. 21. MIT Press, 2020.
ista: Locatello F, Bauer S, Lucic M, Rätsch G, Gelly S, Schölkopf B, Bachem O. 2020.
A sober look at the unsupervised learning of disentangled representations and
their evaluation. Journal of Machine Learning Research. 21, 209.
mla: Locatello, Francesco, et al. “A Sober Look at the Unsupervised Learning of
Disentangled Representations and Their Evaluation.” Journal of Machine Learning
Research, vol. 21, 209, MIT Press, 2020.
short: F. Locatello, S. Bauer, M. Lucic, G. Rätsch, S. Gelly, B. Schölkopf, O. Bachem,
Journal of Machine Learning Research 21 (2020).
date_created: 2023-08-22T14:10:34Z
date_published: 2020-09-01T00:00:00Z
date_updated: 2023-09-12T09:23:56Z
day: '01'
ddc:
- '000'
department:
- _id: FrLo
extern: '1'
external_id:
arxiv:
- '2010.14766'
has_accepted_license: '1'
intvolume: ' 21'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://jmlr.csail.mit.edu/papers/v21/19-976.html
month: '09'
oa: 1
oa_version: Published Version
publication: Journal of Machine Learning Research
publication_status: published
publisher: MIT Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: A sober look at the unsupervised learning of disentangled representations and
their evaluation
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 21
year: '2020'
...
---
_id: '7569'
abstract:
- lang: eng
text: 'Genes differ in the frequency at which they are expressed and in the form
of regulation used to control their activity. In particular, positive or negative
regulation can lead to activation of a gene in response to an external signal.
Previous works proposed that the form of regulation of a gene correlates with
its frequency of usage: positive regulation when the gene is frequently expressed
and negative regulation when infrequently expressed. Such network design means
that, in the absence of their regulators, the genes are found in their least required
activity state, hence regulatory intervention is often necessary. Due to the multitude
of genes and regulators, spurious binding and unbinding events, called “crosstalk”,
could occur. To determine how the form of regulation affects the global crosstalk
in the network, we used a mathematical model that includes multiple regulators
and multiple target genes. We found that crosstalk depends non-monotonically on
the availability of regulators. Our analysis showed that excess use of regulation
entailed by the formerly suggested network design caused high crosstalk levels
in a large part of the parameter space. We therefore considered the opposite ‘idle’
design, where the default unregulated state of genes is their frequently required
activity state. We found, that ‘idle’ design minimized the use of regulation and
thus minimized crosstalk. In addition, we estimated global crosstalk of S. cerevisiae
using transcription factors binding data. We demonstrated that even partial network
data could suffice to estimate its global crosstalk, suggesting its applicability
to additional organisms. We found that S. cerevisiae estimated crosstalk is lower
than that of a random network, suggesting that natural selection reduces crosstalk.
In summary, our study highlights a new type of protein production cost which is
typically overlooked: that of regulatory interference caused by the presence of
excess regulators in the cell. It demonstrates the importance of whole-network
descriptions, which could show effects missed by single-gene models.'
article_number: e1007642
article_processing_charge: No
article_type: original
author:
- first_name: Rok
full_name: Grah, Rok
id: 483E70DE-F248-11E8-B48F-1D18A9856A87
last_name: Grah
orcid: 0000-0003-2539-3560
- first_name: Tamar
full_name: Friedlander, Tamar
last_name: Friedlander
citation:
ama: Grah R, Friedlander T. The relation between crosstalk and gene regulation form
revisited. PLOS Computational Biology. 2020;16(2). doi:10.1371/journal.pcbi.1007642
apa: Grah, R., & Friedlander, T. (2020). The relation between crosstalk and
gene regulation form revisited. PLOS Computational Biology. Public Library
of Science. https://doi.org/10.1371/journal.pcbi.1007642
chicago: Grah, Rok, and Tamar Friedlander. “The Relation between Crosstalk and Gene
Regulation Form Revisited.” PLOS Computational Biology. Public Library
of Science, 2020. https://doi.org/10.1371/journal.pcbi.1007642.
ieee: R. Grah and T. Friedlander, “The relation between crosstalk and gene regulation
form revisited,” PLOS Computational Biology, vol. 16, no. 2. Public Library
of Science, 2020.
ista: Grah R, Friedlander T. 2020. The relation between crosstalk and gene regulation
form revisited. PLOS Computational Biology. 16(2), e1007642.
mla: Grah, Rok, and Tamar Friedlander. “The Relation between Crosstalk and Gene
Regulation Form Revisited.” PLOS Computational Biology, vol. 16, no. 2,
e1007642, Public Library of Science, 2020, doi:10.1371/journal.pcbi.1007642.
short: R. Grah, T. Friedlander, PLOS Computational Biology 16 (2020).
date_created: 2020-03-06T07:39:38Z
date_published: 2020-02-25T00:00:00Z
date_updated: 2023-09-12T11:02:24Z
day: '25'
ddc:
- '000'
- '570'
department:
- _id: CaGu
- _id: GaTk
doi: 10.1371/journal.pcbi.1007642
external_id:
isi:
- '000526725200019'
file:
- access_level: open_access
checksum: 5239dd134dc6e1c71fe7b3ce2953da37
content_type: application/pdf
creator: dernst
date_created: 2020-03-09T15:12:21Z
date_updated: 2020-07-14T12:48:00Z
file_id: '7579'
file_name: 2020_PlosCompBio_Grah.pdf
file_size: 2209325
relation: main_file
file_date_updated: 2020-07-14T12:48:00Z
has_accepted_license: '1'
intvolume: ' 16'
isi: 1
issue: '2'
language:
- iso: eng
month: '02'
oa: 1
oa_version: Published Version
publication: PLOS Computational Biology
publication_identifier:
issn:
- 1553-7358
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
related_material:
record:
- id: '9716'
relation: research_data
status: deleted
- id: '9776'
relation: research_data
status: public
- id: '9779'
relation: used_in_publication
status: public
- id: '8155'
relation: dissertation_contains
status: public
- id: '9777'
relation: research_data
status: public
scopus_import: '1'
status: public
title: The relation between crosstalk and gene regulation form revisited
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 16
year: '2020'
...
---
_id: '8813'
abstract:
- lang: eng
text: 'In mammals, chromatin marks at imprinted genes are asymmetrically inherited
to control parentally-biased gene expression. This control is thought predominantly
to involve parent-specific differentially methylated regions (DMR) in genomic
DNA. However, neither parent-of-origin-specific transcription nor DMRs have been
comprehensively mapped. We here address this by integrating transcriptomic and
epigenomic approaches in mouse preimplantation embryos (blastocysts). Transcriptome-analysis
identified 71 genes expressed with previously unknown parent-of-origin-specific
expression in blastocysts (nBiX: novel blastocyst-imprinted expression). Uniparental
expression of nBiX genes disappeared soon after implantation. Micro-whole-genome
bisulfite sequencing (μWGBS) of individual uniparental blastocysts detected 859
DMRs. Only 18% of nBiXs were associated with a DMR, whereas 60% were associated
with parentally-biased H3K27me3. This suggests a major role for Polycomb-mediated
imprinting in blastocysts. Five nBiX-clusters contained at least one known imprinted
gene, and five novel clusters contained exclusively nBiX-genes. These data suggest
a complex program of stage-specific imprinting involving different tiers of regulation.'
article_processing_charge: No
author:
- first_name: Laura
full_name: Santini, Laura
last_name: Santini
- first_name: Florian
full_name: Halbritter, Florian
last_name: Halbritter
- first_name: Fabian
full_name: Titz-Teixeira, Fabian
last_name: Titz-Teixeira
- first_name: Toru
full_name: Suzuki, Toru
last_name: Suzuki
- first_name: Maki
full_name: Asami, Maki
last_name: Asami
- first_name: Julia
full_name: Ramesmayer, Julia
last_name: Ramesmayer
- first_name: Xiaoyan
full_name: Ma, Xiaoyan
last_name: Ma
- first_name: Andreas
full_name: Lackner, Andreas
last_name: Lackner
- first_name: Nick
full_name: Warr, Nick
last_name: Warr
- first_name: Florian
full_name: Pauler, Florian
id: 48EA0138-F248-11E8-B48F-1D18A9856A87
last_name: Pauler
orcid: 0000-0002-7462-0048
- first_name: Simon
full_name: Hippenmeyer, Simon
id: 37B36620-F248-11E8-B48F-1D18A9856A87
last_name: Hippenmeyer
orcid: 0000-0003-2279-1061
- first_name: Ernest
full_name: Laue, Ernest
last_name: Laue
- first_name: Matthias
full_name: Farlik, Matthias
last_name: Farlik
- first_name: Christoph
full_name: Bock, Christoph
last_name: Bock
- first_name: Andreas
full_name: Beyer, Andreas
last_name: Beyer
- first_name: Anthony C. F.
full_name: Perry, Anthony C. F.
last_name: Perry
- first_name: Martin
full_name: Leeb, Martin
last_name: Leeb
citation:
ama: Santini L, Halbritter F, Titz-Teixeira F, et al. Novel imprints in mouse blastocysts
are predominantly DNA methylation independent. bioRxiv. doi:10.1101/2020.11.03.366948
apa: Santini, L., Halbritter, F., Titz-Teixeira, F., Suzuki, T., Asami, M., Ramesmayer,
J., … Leeb, M. (n.d.). Novel imprints in mouse blastocysts are predominantly DNA
methylation independent. bioRxiv. Cold Spring Harbor Laboratory. https://doi.org/10.1101/2020.11.03.366948
chicago: Santini, Laura, Florian Halbritter, Fabian Titz-Teixeira, Toru Suzuki,
Maki Asami, Julia Ramesmayer, Xiaoyan Ma, et al. “Novel Imprints in Mouse Blastocysts
Are Predominantly DNA Methylation Independent.” BioRxiv. Cold Spring Harbor
Laboratory, n.d. https://doi.org/10.1101/2020.11.03.366948.
ieee: L. Santini et al., “Novel imprints in mouse blastocysts are predominantly
DNA methylation independent,” bioRxiv. Cold Spring Harbor Laboratory.
ista: Santini L, Halbritter F, Titz-Teixeira F, Suzuki T, Asami M, Ramesmayer J,
Ma X, Lackner A, Warr N, Pauler F, Hippenmeyer S, Laue E, Farlik M, Bock C, Beyer
A, Perry ACF, Leeb M. Novel imprints in mouse blastocysts are predominantly DNA
methylation independent. bioRxiv, 10.1101/2020.11.03.366948.
mla: Santini, Laura, et al. “Novel Imprints in Mouse Blastocysts Are Predominantly
DNA Methylation Independent.” BioRxiv, Cold Spring Harbor Laboratory, doi:10.1101/2020.11.03.366948.
short: L. Santini, F. Halbritter, F. Titz-Teixeira, T. Suzuki, M. Asami, J. Ramesmayer,
X. Ma, A. Lackner, N. Warr, F. Pauler, S. Hippenmeyer, E. Laue, M. Farlik, C.
Bock, A. Beyer, A.C.F. Perry, M. Leeb, BioRxiv (n.d.).
date_created: 2020-11-26T07:17:19Z
date_published: 2020-11-05T00:00:00Z
date_updated: 2023-09-12T11:05:28Z
day: '05'
department:
- _id: SiHi
doi: 10.1101/2020.11.03.366948
external_id:
pmid:
- 'PPR234457 '
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1101/2020.11.03.366948
month: '11'
oa: 1
oa_version: Preprint
pmid: 1
publication: bioRxiv
publication_status: submitted
publisher: Cold Spring Harbor Laboratory
status: public
title: Novel imprints in mouse blastocysts are predominantly DNA methylation independent
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2020'
...
---
_id: '9777'
article_processing_charge: No
author:
- first_name: Rok
full_name: Grah, Rok
id: 483E70DE-F248-11E8-B48F-1D18A9856A87
last_name: Grah
orcid: 0000-0003-2539-3560
- first_name: Tamar
full_name: Friedlander, Tamar
last_name: Friedlander
citation:
ama: Grah R, Friedlander T. Maximizing crosstalk. 2020. doi:10.1371/journal.pcbi.1007642.s002
apa: Grah, R., & Friedlander, T. (2020). Maximizing crosstalk. Public Library
of Science. https://doi.org/10.1371/journal.pcbi.1007642.s002
chicago: Grah, Rok, and Tamar Friedlander. “Maximizing Crosstalk.” Public Library
of Science, 2020. https://doi.org/10.1371/journal.pcbi.1007642.s002.
ieee: R. Grah and T. Friedlander, “Maximizing crosstalk.” Public Library of Science,
2020.
ista: Grah R, Friedlander T. 2020. Maximizing crosstalk, Public Library of Science,
10.1371/journal.pcbi.1007642.s002.
mla: Grah, Rok, and Tamar Friedlander. Maximizing Crosstalk. Public Library
of Science, 2020, doi:10.1371/journal.pcbi.1007642.s002.
short: R. Grah, T. Friedlander, (2020).
date_created: 2021-08-06T07:21:51Z
date_published: 2020-02-25T00:00:00Z
date_updated: 2023-09-12T11:02:25Z
day: '25'
department:
- _id: GaTk
doi: 10.1371/journal.pcbi.1007642.s002
main_file_link:
- open_access: '1'
url: https://doi.org/10.1371/journal.pcbi.1007642.s002
month: '02'
oa: 1
oa_version: None
publisher: Public Library of Science
related_material:
record:
- id: '7569'
relation: used_in_publication
status: public
status: public
title: Maximizing crosstalk
type: research_data_reference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2020'
...
---
_id: '8332'
abstract:
- lang: eng
text: "Designing and verifying concurrent programs is a notoriously challenging,
time consuming, and error prone task, even for experts. This is due to the sheer
number of possible interleavings of a concurrent program, all of which have to
be tracked and accounted for in a formal proof. Inventing an inductive invariant
that captures all interleavings of a low-level implementation is theoretically
possible, but practically intractable. We develop a refinement-based verification
framework that provides mechanisms to simplify proof construction by decomposing
the verification task into smaller subtasks.\r\n\r\nIn a first line of work, we
present a foundation for refinement reasoning over structured concurrent programs.
We introduce layered concurrent programs as a compact notation to represent multi-layer
refinement proofs. A layered concurrent program specifies a sequence of connected
concurrent programs, from most concrete to most abstract, such that common parts
of different programs are written exactly once. Each program in this sequence
is expressed as structured concurrent program, i.e., a program over (potentially
recursive) procedures, imperative control flow, gated atomic actions, structured
parallelism, and asynchronous concurrency. This is in contrast to existing refinement-based
verifiers, which represent concurrent systems as flat transition relations. We
present a powerful refinement proof rule that decomposes refinement checking over
structured programs into modular verification conditions. Refinement checking
is supported by a new form of modular, parameterized invariants, called yield
invariants, and a linear permission system to enhance local reasoning.\r\n\r\nIn
a second line of work, we present two new reduction-based program transformations
that target asynchronous programs. These transformations reduce the number of
interleavings that need to be considered, thus reducing the complexity of invariants.
Synchronization simplifies the verification of asynchronous programs by introducing
the fiction, for proof purposes, that asynchronous operations complete synchronously.
Synchronization summarizes an asynchronous computation as immediate atomic effect.
Inductive sequentialization establishes sequential reductions that captures every
behavior of the original program up to reordering of coarse-grained commutative
actions. A sequential reduction of a concurrent program is easy to reason about
since it corresponds to a simple execution of the program in an idealized synchronous
environment, where processes act in a fixed order and at the same speed.\r\n\r\nOur
approach is implemented the CIVL verifier, which has been successfully used for
the verification of several complex concurrent programs. In our methodology, the
overall correctness of a program is established piecemeal by focusing on the invariant
required for each refinement step separately. While the programmer does the creative
work of specifying the chain of programs and the inductive invariant justifying
each link in the chain, the tool automatically constructs the verification conditions
underlying each refinement step."
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Bernhard
full_name: Kragl, Bernhard
id: 320FC952-F248-11E8-B48F-1D18A9856A87
last_name: Kragl
orcid: 0000-0001-7745-9117
citation:
ama: 'Kragl B. Verifying concurrent programs: Refinement, synchronization, sequentialization.
2020. doi:10.15479/AT:ISTA:8332'
apa: 'Kragl, B. (2020). Verifying concurrent programs: Refinement, synchronization,
sequentialization. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:8332'
chicago: 'Kragl, Bernhard. “Verifying Concurrent Programs: Refinement, Synchronization,
Sequentialization.” Institute of Science and Technology Austria, 2020. https://doi.org/10.15479/AT:ISTA:8332.'
ieee: 'B. Kragl, “Verifying concurrent programs: Refinement, synchronization, sequentialization,”
Institute of Science and Technology Austria, 2020.'
ista: 'Kragl B. 2020. Verifying concurrent programs: Refinement, synchronization,
sequentialization. Institute of Science and Technology Austria.'
mla: 'Kragl, Bernhard. Verifying Concurrent Programs: Refinement, Synchronization,
Sequentialization. Institute of Science and Technology Austria, 2020, doi:10.15479/AT:ISTA:8332.'
short: 'B. Kragl, Verifying Concurrent Programs: Refinement, Synchronization, Sequentialization,
Institute of Science and Technology Austria, 2020.'
date_created: 2020-09-04T12:24:12Z
date_published: 2020-09-03T00:00:00Z
date_updated: 2023-09-13T08:45:08Z
day: '03'
ddc:
- '000'
degree_awarded: PhD
department:
- _id: ToHe
doi: 10.15479/AT:ISTA:8332
file:
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checksum: 26fe261550f691280bda4c454bf015c7
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creator: bkragl
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date_created: 2020-09-04T13:00:17Z
date_updated: 2020-09-04T13:00:17Z
file_id: '8335'
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file_date_updated: 2020-09-04T13:00:17Z
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language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
page: '120'
publication_identifier:
issn:
- 2663-337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '133'
relation: part_of_dissertation
status: public
- id: '8012'
relation: part_of_dissertation
status: public
- id: '8195'
relation: part_of_dissertation
status: public
- id: '160'
relation: part_of_dissertation
status: public
status: public
supervisor:
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
title: 'Verifying concurrent programs: Refinement, synchronization, sequentialization'
type: dissertation
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
year: '2020'
...
---
_id: '14326'
abstract:
- lang: eng
text: "Learning object-centric representations of complex scenes is a promising
step towards enabling efficient abstract reasoning from low-level perceptual features.
Yet, most deep learning approaches learn distributed representations that do not
capture the compositional properties of natural scenes. In this paper, we present
the Slot Attention module, an architectural component that interfaces with perceptual
representations such as the output of a convolutional neural network and produces
a set of task-dependent abstract representations which we call slots. These slots
are exchangeable and can bind to any object in the input by specializing through
a competitive procedure over multiple rounds of attention. We empirically demonstrate
that Slot Attention can extract object-centric representations that enable generalization
to unseen compositions when trained on unsupervised object discovery and supervised
property prediction tasks.\r\n\r\n"
article_processing_charge: No
author:
- first_name: Francesco
full_name: Locatello, Francesco
id: 26cfd52f-2483-11ee-8040-88983bcc06d4
last_name: Locatello
orcid: 0000-0002-4850-0683
- first_name: Dirk
full_name: Weissenborn, Dirk
last_name: Weissenborn
- first_name: Thomas
full_name: Unterthiner, Thomas
last_name: Unterthiner
- first_name: Aravindh
full_name: Mahendran, Aravindh
last_name: Mahendran
- first_name: Georg
full_name: Heigold, Georg
last_name: Heigold
- first_name: Jakob
full_name: Uszkoreit, Jakob
last_name: Uszkoreit
- first_name: Alexey
full_name: Dosovitskiy, Alexey
last_name: Dosovitskiy
- first_name: Thomas
full_name: Kipf, Thomas
last_name: Kipf
citation:
ama: 'Locatello F, Weissenborn D, Unterthiner T, et al. Object-centric learning
with slot attention. In: Advances in Neural Information Processing Systems.
Vol 33. Curran Associates; 2020:11525-11538.'
apa: 'Locatello, F., Weissenborn, D., Unterthiner, T., Mahendran, A., Heigold, G.,
Uszkoreit, J., … Kipf, T. (2020). Object-centric learning with slot attention.
In Advances in Neural Information Processing Systems (Vol. 33, pp. 11525–11538).
Virtual: Curran Associates.'
chicago: Locatello, Francesco, Dirk Weissenborn, Thomas Unterthiner, Aravindh Mahendran,
Georg Heigold, Jakob Uszkoreit, Alexey Dosovitskiy, and Thomas Kipf. “Object-Centric
Learning with Slot Attention.” In Advances in Neural Information Processing
Systems, 33:11525–38. Curran Associates, 2020.
ieee: F. Locatello et al., “Object-centric learning with slot attention,”
in Advances in Neural Information Processing Systems, Virtual, 2020, vol.
33, pp. 11525–11538.
ista: 'Locatello F, Weissenborn D, Unterthiner T, Mahendran A, Heigold G, Uszkoreit
J, Dosovitskiy A, Kipf T. 2020. Object-centric learning with slot attention. Advances
in Neural Information Processing Systems. NeurIPS: Neural Information Processing
Systems vol. 33, 11525–11538.'
mla: Locatello, Francesco, et al. “Object-Centric Learning with Slot Attention.”
Advances in Neural Information Processing Systems, vol. 33, Curran Associates,
2020, pp. 11525–38.
short: F. Locatello, D. Weissenborn, T. Unterthiner, A. Mahendran, G. Heigold, J.
Uszkoreit, A. Dosovitskiy, T. Kipf, in:, Advances in Neural Information Processing
Systems, Curran Associates, 2020, pp. 11525–11538.
conference:
end_date: 2020-12-12
location: Virtual
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2020-12-06
date_created: 2023-09-13T12:03:46Z
date_published: 2020-01-01T00:00:00Z
date_updated: 2023-09-13T12:19:19Z
department:
- _id: FrLo
extern: '1'
external_id:
arxiv:
- '2006.15055'
intvolume: ' 33'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2006.15055
oa: 1
oa_version: Preprint
page: 11525-11538
publication: Advances in Neural Information Processing Systems
publication_identifier:
isbn:
- '9781713829546'
publication_status: published
publisher: Curran Associates
quality_controlled: '1'
status: public
title: Object-centric learning with slot attention
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 33
year: '2020'
...
---
_id: '71'
abstract:
- lang: eng
text: "We consider dynamical transport metrics for probability measures on discretisations
of a bounded convex domain in ℝd. These metrics are natural discrete counterparts
to the Kantorovich metric \U0001D54E2, defined using a Benamou-Brenier type formula.
Under mild assumptions we prove an asymptotic upper bound for the discrete transport
metric Wt in terms of \U0001D54E2, as the size of the mesh T tends to 0. However,
we show that the corresponding lower bound may fail in general, even on certain
one-dimensional and symmetric two-dimensional meshes. In addition, we show that
the asymptotic lower bound holds under an isotropy assumption on the mesh, which
turns out to be essentially necessary. This assumption is satisfied, e.g., for
tilings by convex regular polygons, and it implies Gromov-Hausdorff convergence
of the transport metric."
article_processing_charge: No
article_type: original
author:
- first_name: Peter
full_name: Gladbach, Peter
last_name: Gladbach
- first_name: Eva
full_name: Kopfer, Eva
last_name: Kopfer
- first_name: Jan
full_name: Maas, Jan
id: 4C5696CE-F248-11E8-B48F-1D18A9856A87
last_name: Maas
orcid: 0000-0002-0845-1338
citation:
ama: Gladbach P, Kopfer E, Maas J. Scaling limits of discrete optimal transport.
SIAM Journal on Mathematical Analysis. 2020;52(3):2759-2802. doi:10.1137/19M1243440
apa: Gladbach, P., Kopfer, E., & Maas, J. (2020). Scaling limits of discrete
optimal transport. SIAM Journal on Mathematical Analysis. Society for Industrial
and Applied Mathematics. https://doi.org/10.1137/19M1243440
chicago: Gladbach, Peter, Eva Kopfer, and Jan Maas. “Scaling Limits of Discrete
Optimal Transport.” SIAM Journal on Mathematical Analysis. Society for
Industrial and Applied Mathematics, 2020. https://doi.org/10.1137/19M1243440.
ieee: P. Gladbach, E. Kopfer, and J. Maas, “Scaling limits of discrete optimal transport,”
SIAM Journal on Mathematical Analysis, vol. 52, no. 3. Society for Industrial
and Applied Mathematics, pp. 2759–2802, 2020.
ista: Gladbach P, Kopfer E, Maas J. 2020. Scaling limits of discrete optimal transport.
SIAM Journal on Mathematical Analysis. 52(3), 2759–2802.
mla: Gladbach, Peter, et al. “Scaling Limits of Discrete Optimal Transport.” SIAM
Journal on Mathematical Analysis, vol. 52, no. 3, Society for Industrial and
Applied Mathematics, 2020, pp. 2759–802, doi:10.1137/19M1243440.
short: P. Gladbach, E. Kopfer, J. Maas, SIAM Journal on Mathematical Analysis 52
(2020) 2759–2802.
date_created: 2018-12-11T11:44:28Z
date_published: 2020-10-01T00:00:00Z
date_updated: 2023-09-18T08:13:15Z
day: '01'
department:
- _id: JaMa
doi: 10.1137/19M1243440
external_id:
arxiv:
- '1809.01092'
isi:
- '000546975100017'
intvolume: ' 52'
isi: 1
issue: '3'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1809.01092
month: '10'
oa: 1
oa_version: Preprint
page: 2759-2802
publication: SIAM Journal on Mathematical Analysis
publication_identifier:
eissn:
- '10957154'
issn:
- '00361410'
publication_status: published
publisher: Society for Industrial and Applied Mathematics
publist_id: '7983'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Scaling limits of discrete optimal transport
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 52
year: '2020'
...
---
_id: '5681'
abstract:
- lang: eng
text: 'We introduce dynamically warping grids for adaptive liquid simulation. Our
primary contributions are a strategy for dynamically deforming regular grids over
the course of a simulation and a method for efficiently utilizing these deforming
grids for liquid simulation. Prior work has shown that unstructured grids are
very effective for adaptive fluid simulations. However, unstructured grids often
lead to complicated implementations and a poor cache hit rate due to inconsistent
memory access. Regular grids, on the other hand, provide a fast, fixed memory
access pattern and straightforward implementation. Our method combines the advantages
of both: we leverage the simplicity of regular grids while still achieving practical
and controllable spatial adaptivity. We demonstrate that our method enables adaptive
simulations that are fast, flexible, and robust to null-space issues. At the same
time, our method is simple to implement and takes advantage of existing highly-tuned
algorithms.'
acknowledged_ssus:
- _id: ScienComp
acknowledgement: This work was partially supported by JSPS Grant-in-Aid forYoung Scientists
(Start-up) 16H07410, the ERC StartingGrantsrealFlow(StG-2015-637014) andBigSplash(StG-2014-638176).
This research was supported by the Scientific Ser-vice Units (SSU) of IST Austria
through resources providedby Scientific Computing. We would like to express my grati-tude
to Nobuyuki Umetani and Tomas Skrivan for insight-ful discussion.
article_processing_charge: No
article_type: original
author:
- first_name: Ibayashi
full_name: Hikaru, Ibayashi
last_name: Hikaru
- first_name: Christopher J
full_name: Wojtan, Christopher J
id: 3C61F1D2-F248-11E8-B48F-1D18A9856A87
last_name: Wojtan
orcid: 0000-0001-6646-5546
- first_name: Nils
full_name: Thuerey, Nils
last_name: Thuerey
- first_name: Takeo
full_name: Igarashi, Takeo
last_name: Igarashi
- first_name: Ryoichi
full_name: Ando, Ryoichi
last_name: Ando
citation:
ama: Hikaru I, Wojtan C, Thuerey N, Igarashi T, Ando R. Simulating liquids on dynamically
warping grids. IEEE Transactions on Visualization and Computer Graphics.
2020;26(6):2288-2302. doi:10.1109/TVCG.2018.2883628
apa: Hikaru, I., Wojtan, C., Thuerey, N., Igarashi, T., & Ando, R. (2020). Simulating
liquids on dynamically warping grids. IEEE Transactions on Visualization and
Computer Graphics. IEEE. https://doi.org/10.1109/TVCG.2018.2883628
chicago: Hikaru, Ibayashi, Chris Wojtan, Nils Thuerey, Takeo Igarashi, and Ryoichi
Ando. “Simulating Liquids on Dynamically Warping Grids.” IEEE Transactions
on Visualization and Computer Graphics. IEEE, 2020. https://doi.org/10.1109/TVCG.2018.2883628.
ieee: I. Hikaru, C. Wojtan, N. Thuerey, T. Igarashi, and R. Ando, “Simulating liquids
on dynamically warping grids,” IEEE Transactions on Visualization and Computer
Graphics, vol. 26, no. 6. IEEE, pp. 2288–2302, 2020.
ista: Hikaru I, Wojtan C, Thuerey N, Igarashi T, Ando R. 2020. Simulating liquids
on dynamically warping grids. IEEE Transactions on Visualization and Computer
Graphics. 26(6), 2288–2302.
mla: Hikaru, Ibayashi, et al. “Simulating Liquids on Dynamically Warping Grids.”
IEEE Transactions on Visualization and Computer Graphics, vol. 26, no.
6, IEEE, 2020, pp. 2288–302, doi:10.1109/TVCG.2018.2883628.
short: I. Hikaru, C. Wojtan, N. Thuerey, T. Igarashi, R. Ando, IEEE Transactions
on Visualization and Computer Graphics 26 (2020) 2288–2302.
date_created: 2018-12-16T22:59:21Z
date_published: 2020-06-01T00:00:00Z
date_updated: 2023-09-18T09:30:01Z
day: '01'
ddc:
- '006'
department:
- _id: ChWo
doi: 10.1109/TVCG.2018.2883628
external_id:
isi:
- '000532295600014'
pmid:
- '30507534'
file:
- access_level: open_access
checksum: 8d4c55443a0ee335bb5bb652de503042
content_type: application/pdf
creator: wojtan
date_created: 2020-10-08T08:34:53Z
date_updated: 2020-10-08T08:34:53Z
file_id: '8626'
file_name: preprint.pdf
file_size: 21910098
relation: main_file
success: 1
file_date_updated: 2020-10-08T08:34:53Z
has_accepted_license: '1'
intvolume: ' 26'
isi: 1
issue: '6'
language:
- iso: eng
month: '06'
oa: 1
oa_version: Submitted Version
page: 2288-2302
pmid: 1
publication: IEEE Transactions on Visualization and Computer Graphics
publication_identifier:
eissn:
- '19410506'
issn:
- '10772626'
publication_status: published
publisher: IEEE
quality_controlled: '1'
scopus_import: '1'
status: public
title: Simulating liquids on dynamically warping grids
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 26
year: '2020'
...
---
_id: '8958'
abstract:
- lang: eng
text: "The oft-quoted dictum by Arthur Schawlow: ``A diatomic molecule has one atom
too many'' has been disavowed. Inspired by the possibility to experimentally manipulate
and enhance chemical reactivity in helium nanodroplets, we investigate the rotation
of coupled cold molecules in the presence of a many-body environment.\r\nIn this
thesis, we introduce new variational approaches to quantum impurities and apply
them to the Fröhlich polaron - a quasiparticle formed out of an electron (or other
point-like impurity) in a polar medium, and to the angulon - a quasiparticle formed
out of a rotating molecule in a bosonic bath.\r\nWith this theoretical toolbox,
we reveal the self-localization transition for the angulon quasiparticle. We show
that, unlike for polarons, self-localization of angulons occurs at finite impurity-bath
coupling already at the mean-field level. The transition is accompanied by the
spherical-symmetry breaking of the angulon ground state and a discontinuity in
the first derivative of the ground-state energy. Moreover, the type of symmetry
breaking is dictated by the symmetry of the microscopic impurity-bath interaction,
which leads to a number of distinct self-localized states. \r\nFor the system
containing multiple impurities, by analogy with the bipolaron, we introduce the
biangulon quasiparticle describing two rotating molecules that align with respect
to each other due to the effective attractive interaction mediated by the excitations
of the bath. We study this system from the strong-coupling regime to the weak
molecule-bath interaction regime. We show that the molecules tend to have a strong
alignment in the ground state, the biangulon shows shifted angulon instabilities
and an additional spectral instability, where resonant angular momentum transfer
between the molecules and the bath takes place. Finally, we introduce a diagonalization
scheme that allows us to describe the transition from two separated angulons to
a biangulon as a function of the distance between the two molecules."
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Xiang
full_name: Li, Xiang
id: 4B7E523C-F248-11E8-B48F-1D18A9856A87
last_name: Li
citation:
ama: Li X. Rotation of coupled cold molecules in the presence of a many-body environment.
2020. doi:10.15479/AT:ISTA:8958
apa: Li, X. (2020). Rotation of coupled cold molecules in the presence of a many-body
environment. Institute of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:8958
chicago: Li, Xiang. “Rotation of Coupled Cold Molecules in the Presence of a Many-Body
Environment.” Institute of Science and Technology Austria, 2020. https://doi.org/10.15479/AT:ISTA:8958.
ieee: X. Li, “Rotation of coupled cold molecules in the presence of a many-body
environment,” Institute of Science and Technology Austria, 2020.
ista: Li X. 2020. Rotation of coupled cold molecules in the presence of a many-body
environment. Institute of Science and Technology Austria.
mla: Li, Xiang. Rotation of Coupled Cold Molecules in the Presence of a Many-Body
Environment. Institute of Science and Technology Austria, 2020, doi:10.15479/AT:ISTA:8958.
short: X. Li, Rotation of Coupled Cold Molecules in the Presence of a Many-Body
Environment, Institute of Science and Technology Austria, 2020.
date_created: 2020-12-21T09:44:30Z
date_published: 2020-12-21T00:00:00Z
date_updated: 2023-09-20T11:30:58Z
day: '21'
ddc:
- '539'
degree_awarded: PhD
department:
- _id: MiLe
doi: 10.15479/AT:ISTA:8958
ec_funded: 1
file:
- access_level: open_access
checksum: 3994c54a1241451d561db1d4f43bad30
content_type: application/pdf
creator: xli
date_created: 2020-12-22T10:55:56Z
date_updated: 2020-12-22T10:55:56Z
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content_type: application/x-zip-compressed
creator: xli
date_created: 2020-12-22T10:56:03Z
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file_id: '8968'
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file_size: 4018859
relation: source_file
file_date_updated: 2020-12-30T07:18:03Z
has_accepted_license: '1'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
page: '125'
project:
- _id: 26031614-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P29902
name: Quantum rotations in the presence of a many-body environment
- _id: 2688CF98-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '801770'
name: 'Angulon: physics and applications of a new quasiparticle'
publication_identifier:
issn:
- 2663-337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '5886'
relation: part_of_dissertation
status: public
- id: '8587'
relation: part_of_dissertation
status: public
- id: '1120'
relation: part_of_dissertation
status: public
status: public
supervisor:
- first_name: Mikhail
full_name: Lemeshko, Mikhail
id: 37CB05FA-F248-11E8-B48F-1D18A9856A87
last_name: Lemeshko
orcid: 0000-0002-6990-7802
title: Rotation of coupled cold molecules in the presence of a many-body environment
type: dissertation
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
year: '2020'
...
---
_id: '8386'
abstract:
- lang: eng
text: "Form versus function is a long-standing debate in various design-related
fields, such as architecture as well as graphic and industrial design. A good
design that balances form and function often requires considerable human effort
and collaboration among experts from different professional fields. Computational
design tools provide a new paradigm for designing functional objects. In computational
design, form and function are represented as mathematical\r\nquantities, with
the help of numerical and combinatorial algorithms, they can assist even novice
users in designing versatile models that exhibit their desired functionality.
This thesis presents three disparate research studies on the computational design
of functional objects: The appearance of 3d print—we optimize the volumetric material
distribution for faithfully replicating colored surface texture in 3d printing;
the dynamic motion of mechanical structures—\r\nour design system helps the novice
user to retarget various mechanical templates with different functionality to
complex 3d shapes; and a more abstract functionality, multistability—our algorithm
automatically generates models that exhibit multiple stable target poses. For
each of these cases, our computational design tools not only ensure the functionality
of the results but also permit the user aesthetic freedom over the form. Moreover,
fabrication constraints\r\nwere taken into account, which allow for the immediate
creation of physical realization via 3D printing or laser cutting."
acknowledged_ssus:
- _id: SSU
acknowledgement: The research in this thesis has received funding from the European
Union’s Horizon 2020 research and innovation programme, under the Marie Skłodowska-Curie
grant agreement No 642841 (DISTRO) and the European Research Council grant agreement
No 715767 (MATERIALIZABLE). All the research projects in this thesis were also supported
by Scientific Service Units (SSUs) at IST Austria.
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Ran
full_name: Zhang, Ran
id: 4DDBCEB0-F248-11E8-B48F-1D18A9856A87
last_name: Zhang
orcid: 0000-0002-3808-281X
citation:
ama: Zhang R. Structure-aware computational design and its application to 3D printable
volume scattering, mechanism, and multistability. 2020. doi:10.15479/AT:ISTA:8386
apa: Zhang, R. (2020). Structure-aware computational design and its application
to 3D printable volume scattering, mechanism, and multistability. Institute
of Science and Technology Austria. https://doi.org/10.15479/AT:ISTA:8386
chicago: Zhang, Ran. “Structure-Aware Computational Design and Its Application to
3D Printable Volume Scattering, Mechanism, and Multistability.” Institute of Science
and Technology Austria, 2020. https://doi.org/10.15479/AT:ISTA:8386.
ieee: R. Zhang, “Structure-aware computational design and its application to 3D
printable volume scattering, mechanism, and multistability,” Institute of Science
and Technology Austria, 2020.
ista: Zhang R. 2020. Structure-aware computational design and its application to
3D printable volume scattering, mechanism, and multistability. Institute of Science
and Technology Austria.
mla: Zhang, Ran. Structure-Aware Computational Design and Its Application to
3D Printable Volume Scattering, Mechanism, and Multistability. Institute of
Science and Technology Austria, 2020, doi:10.15479/AT:ISTA:8386.
short: R. Zhang, Structure-Aware Computational Design and Its Application to 3D
Printable Volume Scattering, Mechanism, and Multistability, Institute of Science
and Technology Austria, 2020.
date_created: 2020-09-14T01:04:53Z
date_published: 2020-09-14T00:00:00Z
date_updated: 2023-09-22T09:49:31Z
day: '14'
ddc:
- '003'
degree_awarded: PhD
department:
- _id: BeBi
doi: 10.15479/AT:ISTA:8386
ec_funded: 1
file:
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checksum: edcf578b6e1c9b0dd81ff72d319b66ba
content_type: application/x-zip-compressed
creator: rzhang
date_created: 2020-09-14T01:02:59Z
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file_name: PhD_thesis_Ran Zhang_20200915.pdf
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relation: main_file
success: 1
file_date_updated: 2020-09-15T12:51:53Z
has_accepted_license: '1'
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
page: '148'
project:
- _id: 2508E324-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '642841'
name: Distributed 3D Object Design
- _id: 24F9549A-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '715767'
name: 'MATERIALIZABLE: Intelligent fabrication-oriented Computational Design and
Modeling'
publication_identifier:
issn:
- 2663-337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '486'
relation: part_of_dissertation
status: public
- id: '1002'
relation: part_of_dissertation
status: public
status: public
supervisor:
- first_name: Bernd
full_name: Bickel, Bernd
id: 49876194-F248-11E8-B48F-1D18A9856A87
last_name: Bickel
orcid: 0000-0001-6511-9385
title: Structure-aware computational design and its application to 3D printable volume
scattering, mechanism, and multistability
type: dissertation
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
year: '2020'
...
---
_id: '7996'
abstract:
- lang: eng
text: "Quantum computation enables the execution of algorithms that have exponential
complexity. This might open the path towards the synthesis of new materials or
medical drugs, optimization of transport or financial strategies etc., intractable
on even the fastest classical computers. A quantum computer consists of interconnected
two level quantum systems, called qubits, that satisfy DiVincezo’s criteria. Worldwide,
there are ongoing efforts to find the qubit architecture which will unite quantum
error correction compatible single and two qubit fidelities, long distance qubit
to qubit coupling and \r\n calability. Superconducting qubits have gone the furthest
in this race, demonstrating an algorithm running on 53 coupled qubits, but still
the fidelities are not even close to those required for realizing a single logical
qubit. emiconductor qubits offer extremely good characteristics, but they are
currently investigated across different platforms. Uniting those good characteristics
into a single platform might be a big step towards the quantum computer realization.\r\nHere
we describe the implementation of a hole spin qubit hosted in a Ge hut wire double
quantum dot. The high and tunable spin-orbit coupling together with a heavy hole
state character is expected to allow fast spin manipulation and long coherence
times. Furthermore large lever arms, for hut wire devices, should allow good coupling
to superconducting resonators enabling efficient long distance spin to spin coupling
and a sensitive gate reflectometry spin readout. The developed cryogenic setup
(printed circuit board sample holders, filtering, high-frequency wiring) enabled
us to perform low temperature spin dynamics experiments. Indeed, we measured the
fastest single spin qubit Rabi frequencies reported so far, reaching 140 MHz,
while the dephasing times of 130 ns oppose the long decoherence predictions. In
order to further investigate this, a double quantum dot gate was connected directly
to a lumped element\r\nresonator which enabled gate reflectometry readout. The
vanishing inter-dot transition signal, for increasing external magnetic field,
revealed the spin nature of the measured quantity."
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Josip
full_name: Kukucka, Josip
id: 3F5D8856-F248-11E8-B48F-1D18A9856A87
last_name: Kukucka
citation:
ama: Kukucka J. Implementation of a hole spin qubit in Ge hut wires and dispersive
spin sensing. 2020. doi:10.15479/AT:ISTA:7996
apa: Kukucka, J. (2020). Implementation of a hole spin qubit in Ge hut wires
and dispersive spin sensing. Institute of Science and Technology Austria.
https://doi.org/10.15479/AT:ISTA:7996
chicago: Kukucka, Josip. “Implementation of a Hole Spin Qubit in Ge Hut Wires and
Dispersive Spin Sensing.” Institute of Science and Technology Austria, 2020. https://doi.org/10.15479/AT:ISTA:7996.
ieee: J. Kukucka, “Implementation of a hole spin qubit in Ge hut wires and dispersive
spin sensing,” Institute of Science and Technology Austria, 2020.
ista: Kukucka J. 2020. Implementation of a hole spin qubit in Ge hut wires and dispersive
spin sensing. Institute of Science and Technology Austria.
mla: Kukucka, Josip. Implementation of a Hole Spin Qubit in Ge Hut Wires and
Dispersive Spin Sensing. Institute of Science and Technology Austria, 2020,
doi:10.15479/AT:ISTA:7996.
short: J. Kukucka, Implementation of a Hole Spin Qubit in Ge Hut Wires and Dispersive
Spin Sensing, Institute of Science and Technology Austria, 2020.
date_created: 2020-06-22T09:22:23Z
date_published: 2020-06-22T00:00:00Z
date_updated: 2023-09-26T15:50:22Z
day: '22'
ddc:
- '530'
degree_awarded: PhD
department:
- _id: GeKa
doi: 10.15479/AT:ISTA:7996
file:
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checksum: 467e52feb3e361ce8cf5fe8d5c254ece
content_type: application/x-zip-compressed
creator: dernst
date_created: 2020-06-22T09:22:04Z
date_updated: 2020-07-14T12:48:07Z
file_id: '7997'
file_name: JK_thesis_latex_source_files.zip
file_size: 392794743
relation: main_file
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checksum: 1de716bf110dbd77d383e479232bf496
content_type: application/pdf
creator: dernst
date_created: 2020-06-22T09:21:29Z
date_updated: 2020-07-14T12:48:07Z
file_id: '7998'
file_name: PhD_thesis_JK_pdfa.pdf
file_size: 28453247
relation: main_file
file_date_updated: 2020-07-14T12:48:07Z
has_accepted_license: '1'
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
page: '178'
publication_identifier:
issn:
- 2663-337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '1328'
relation: part_of_dissertation
status: public
- id: '7541'
relation: part_of_dissertation
status: public
- id: '77'
relation: part_of_dissertation
status: public
- id: '23'
relation: part_of_dissertation
status: public
- id: '840'
relation: part_of_dissertation
status: public
status: public
supervisor:
- first_name: Georgios
full_name: Katsaros, Georgios
id: 38DB5788-F248-11E8-B48F-1D18A9856A87
last_name: Katsaros
orcid: 0000-0001-8342-202X
title: Implementation of a hole spin qubit in Ge hut wires and dispersive spin sensing
type: dissertation
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
year: '2020'
...