---
_id: '12919'
abstract:
- lang: eng
text: We report the visible light photocatalytic cleavage of trityl thioethers or
ethers under pH-neutral conditions. The method results in the formation of the
respective symmetrical disulfides and alcohols in moderate to excellent yield.
The protocol only requires the addition of a suitable photocatalyst and light
rendering it orthogonal to several functionalities, including acid labile protective
groups. The same conditions can be used to directly convert trityl-protected thiols
into unsymmetrical disulfides or selenosulfides, and to cleave trityl resins in
solid phase organic synthesis.
article_processing_charge: No
article_type: original
author:
- first_name: Sho
full_name: Murakami, Sho
last_name: Murakami
- first_name: Cosima
full_name: Brudy, Cosima
last_name: Brudy
- first_name: Moritz
full_name: Bachmann, Moritz
last_name: Bachmann
- first_name: Yoshiji
full_name: Takemoto, Yoshiji
last_name: Takemoto
- first_name: Bartholomäus
full_name: Pieber, Bartholomäus
id: 93e5e5b2-0da6-11ed-8a41-af589a024726
last_name: Pieber
orcid: 0000-0001-8689-388X
citation:
ama: Murakami S, Brudy C, Bachmann M, Takemoto Y, Pieber B. Photocatalytic cleavage
of trityl protected thiols and alcohols. Synthesis. 2023;55(09):1367-1374.
doi:10.1055/a-1979-5933
apa: Murakami, S., Brudy, C., Bachmann, M., Takemoto, Y., & Pieber, B. (2023).
Photocatalytic cleavage of trityl protected thiols and alcohols. Synthesis.
Georg Thieme Verlag. https://doi.org/10.1055/a-1979-5933
chicago: Murakami, Sho, Cosima Brudy, Moritz Bachmann, Yoshiji Takemoto, and Bartholomäus
Pieber. “Photocatalytic Cleavage of Trityl Protected Thiols and Alcohols.” Synthesis.
Georg Thieme Verlag, 2023. https://doi.org/10.1055/a-1979-5933.
ieee: S. Murakami, C. Brudy, M. Bachmann, Y. Takemoto, and B. Pieber, “Photocatalytic
cleavage of trityl protected thiols and alcohols,” Synthesis, vol. 55,
no. 09. Georg Thieme Verlag, pp. 1367–1374, 2023.
ista: Murakami S, Brudy C, Bachmann M, Takemoto Y, Pieber B. 2023. Photocatalytic
cleavage of trityl protected thiols and alcohols. Synthesis. 55(09), 1367–1374.
mla: Murakami, Sho, et al. “Photocatalytic Cleavage of Trityl Protected Thiols and
Alcohols.” Synthesis, vol. 55, no. 09, Georg Thieme Verlag, 2023, pp. 1367–74,
doi:10.1055/a-1979-5933.
short: S. Murakami, C. Brudy, M. Bachmann, Y. Takemoto, B. Pieber, Synthesis 55
(2023) 1367–1374.
date_created: 2023-05-08T08:25:08Z
date_published: 2023-05-01T00:00:00Z
date_updated: 2023-05-15T08:43:50Z
day: '01'
doi: 10.1055/a-1979-5933
extern: '1'
intvolume: ' 55'
issue: '09'
keyword:
- Organic Chemistry
- Catalysis
language:
- iso: eng
month: '05'
oa_version: None
page: 1367-1374
publication: Synthesis
publication_identifier:
eissn:
- 1437-210X
issn:
- 0039-7881
publication_status: published
publisher: Georg Thieme Verlag
quality_controlled: '1'
scopus_import: '1'
status: public
title: Photocatalytic cleavage of trityl protected thiols and alcohols
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 55
year: '2023'
...
---
_id: '13048'
abstract:
- lang: eng
text: In this paper we introduce a pruning of the medial axis called the (λ,α)-medial
axis (axλα). We prove that the (λ,α)-medial axis of a set K is stable in a Gromov-Hausdorff
sense under weak assumptions. More formally we prove that if K and K′ are close
in the Hausdorff (dH) sense then the (λ,α)-medial axes of K and K′ are close as
metric spaces, that is the Gromov-Hausdorff distance (dGH) between the two is
1/4-Hölder in the sense that dGH (axλα(K),axλα(K′)) ≲ dH(K,K′)1/4. The Hausdorff
distance between the two medial axes is also bounded, by dH (axλα(K),λα(K′)) ≲
dH(K,K′)1/2. These quantified stability results provide guarantees for practical
computations of medial axes from approximations. Moreover, they provide key ingredients
for studying the computability of the medial axis in the context of computable
analysis.
acknowledgement: "We are greatly indebted to Erin Chambers for posing a number of
questions that eventually led to this paper. We would also like to thank the other
organizers of the workshop on ‘Algorithms\r\nfor the medial axis’. We are also indebted
to Tatiana Ezubova for helping with the search for and translation of Russian literature.
The second author thanks all members of the Edelsbrunner and Datashape groups for
the atmosphere in which the research was conducted.\r\nThe research leading to these
results has received funding from the European Research Council (ERC) under the
European Union’s Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement
No. 339025 GUDHI (Algorithmic Foundations of Geometry Understanding in Higher Dimensions).
Supported by the European Union’s Horizon 2020 research and innovation programme
under the Marie Skłodowska-Curie grant agreement No. 754411. The Austrian science
fund (FWF) M-3073."
article_processing_charge: No
author:
- first_name: André
full_name: Lieutier, André
last_name: Lieutier
- first_name: Mathijs
full_name: Wintraecken, Mathijs
id: 307CFBC8-F248-11E8-B48F-1D18A9856A87
last_name: Wintraecken
orcid: 0000-0002-7472-2220
citation:
ama: 'Lieutier A, Wintraecken M. Hausdorff and Gromov-Hausdorff stable subsets of
the medial axis. In: Proceedings of the 55th Annual ACM Symposium on Theory
of Computing. Association for Computing Machinery; 2023:1768-1776. doi:10.1145/3564246.3585113'
apa: 'Lieutier, A., & Wintraecken, M. (2023). Hausdorff and Gromov-Hausdorff
stable subsets of the medial axis. In Proceedings of the 55th Annual ACM Symposium
on Theory of Computing (pp. 1768–1776). Orlando, FL, United States: Association
for Computing Machinery. https://doi.org/10.1145/3564246.3585113'
chicago: Lieutier, André, and Mathijs Wintraecken. “Hausdorff and Gromov-Hausdorff
Stable Subsets of the Medial Axis.” In Proceedings of the 55th Annual ACM Symposium
on Theory of Computing, 1768–76. Association for Computing Machinery, 2023.
https://doi.org/10.1145/3564246.3585113.
ieee: A. Lieutier and M. Wintraecken, “Hausdorff and Gromov-Hausdorff stable subsets
of the medial axis,” in Proceedings of the 55th Annual ACM Symposium on Theory
of Computing, Orlando, FL, United States, 2023, pp. 1768–1776.
ista: 'Lieutier A, Wintraecken M. 2023. Hausdorff and Gromov-Hausdorff stable subsets
of the medial axis. Proceedings of the 55th Annual ACM Symposium on Theory of
Computing. STOC: Symposium on Theory of Computing, 1768–1776.'
mla: Lieutier, André, and Mathijs Wintraecken. “Hausdorff and Gromov-Hausdorff Stable
Subsets of the Medial Axis.” Proceedings of the 55th Annual ACM Symposium on
Theory of Computing, Association for Computing Machinery, 2023, pp. 1768–76,
doi:10.1145/3564246.3585113.
short: A. Lieutier, M. Wintraecken, in:, Proceedings of the 55th Annual ACM Symposium
on Theory of Computing, Association for Computing Machinery, 2023, pp. 1768–1776.
conference:
end_date: 2023-06-23
location: Orlando, FL, United States
name: 'STOC: Symposium on Theory of Computing'
start_date: 2023-06-20
date_created: 2023-05-22T08:02:02Z
date_published: 2023-06-02T00:00:00Z
date_updated: 2023-05-22T08:15:19Z
day: '02'
department:
- _id: HeEd
doi: 10.1145/3564246.3585113
ec_funded: 1
external_id:
arxiv:
- '2303.04014'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2303.04014
month: '06'
oa: 1
oa_version: Preprint
page: 1768-1776
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
- _id: fc390959-9c52-11eb-aca3-afa58bd282b2
grant_number: M03073
name: Learning and triangulating manifolds via collapses
publication: Proceedings of the 55th Annual ACM Symposium on Theory of Computing
publication_identifier:
isbn:
- '9781450399135'
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
status: public
title: Hausdorff and Gromov-Hausdorff stable subsets of the medial axis
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2023'
...
---
_id: '13053'
abstract:
- lang: eng
text: 'Deep neural networks (DNNs) often have to be compressed, via pruning and/or
quantization, before they can be deployed in practical settings. In this work
we propose a new compression-aware minimizer dubbed CrAM that modifies the optimization
step in a principled way, in order to produce models whose local loss behavior
is stable under compression operations such as pruning. Thus, dense models trained
via CrAM should be compressible post-training, in a single step, without significant
accuracy loss. Experimental results on standard benchmarks, such as residual networks
for ImageNet classification and BERT models for language modelling, show that
CrAM produces dense models that can be more accurate than the standard SGD/Adam-based
baselines, but which are stable under weight pruning: specifically, we can prune
models in one-shot to 70-80% sparsity with almost no accuracy loss, and to 90%
with reasonable (∼1%) accuracy loss, which is competitive with gradual compression
methods. Additionally, CrAM can produce sparse models which perform well for transfer
learning, and it also works for semi-structured 2:4 pruning patterns supported
by GPU hardware. The code for reproducing the results is available at this https
URL .'
acknowledged_ssus:
- _id: ScienComp
acknowledgement: "AP, EK, DA received funding from the European Research Council (ERC)
under the European\r\nUnion’s Horizon 2020 research and innovation programme (grant
agreement No 805223 ScaleML). AV acknowledges the support of the French Agence Nationale
de la Recherche (ANR), under grant ANR-21-CE48-0016 (project COMCOPT). We further
acknowledge the support from the Scientific Service Units (SSU) of ISTA through
resources provided by Scientific Computing (SciComp)-"
article_processing_charge: No
author:
- first_name: Elena-Alexandra
full_name: Peste, Elena-Alexandra
id: 32D78294-F248-11E8-B48F-1D18A9856A87
last_name: Peste
- first_name: Adrian
full_name: Vladu, Adrian
last_name: Vladu
- first_name: Eldar
full_name: Kurtic, Eldar
id: 47beb3a5-07b5-11eb-9b87-b108ec578218
last_name: Kurtic
- first_name: Christoph
full_name: Lampert, Christoph
id: 40C20FD2-F248-11E8-B48F-1D18A9856A87
last_name: Lampert
orcid: 0000-0001-8622-7887
- first_name: Dan-Adrian
full_name: Alistarh, Dan-Adrian
id: 4A899BFC-F248-11E8-B48F-1D18A9856A87
last_name: Alistarh
orcid: 0000-0003-3650-940X
citation:
ama: 'Peste E-A, Vladu A, Kurtic E, Lampert C, Alistarh D-A. CrAM: A Compression-Aware
Minimizer. In: 11th International Conference on Learning Representations .'
apa: 'Peste, E.-A., Vladu, A., Kurtic, E., Lampert, C., & Alistarh, D.-A. (n.d.).
CrAM: A Compression-Aware Minimizer. In 11th International Conference on Learning
Representations . Kigali, Rwanda .'
chicago: 'Peste, Elena-Alexandra, Adrian Vladu, Eldar Kurtic, Christoph Lampert,
and Dan-Adrian Alistarh. “CrAM: A Compression-Aware Minimizer.” In 11th International
Conference on Learning Representations , n.d.'
ieee: 'E.-A. Peste, A. Vladu, E. Kurtic, C. Lampert, and D.-A. Alistarh, “CrAM:
A Compression-Aware Minimizer,” in 11th International Conference on Learning
Representations , Kigali, Rwanda .'
ista: 'Peste E-A, Vladu A, Kurtic E, Lampert C, Alistarh D-A. CrAM: A Compression-Aware
Minimizer. 11th International Conference on Learning Representations . ICLR: International
Conference on Learning Representations.'
mla: 'Peste, Elena-Alexandra, et al. “CrAM: A Compression-Aware Minimizer.” 11th
International Conference on Learning Representations .'
short: E.-A. Peste, A. Vladu, E. Kurtic, C. Lampert, D.-A. Alistarh, in:, 11th International
Conference on Learning Representations , n.d.
conference:
end_date: 2023-05-05
location: 'Kigali, Rwanda '
name: 'ICLR: International Conference on Learning Representations'
start_date: 2023-05-01
date_created: 2023-05-23T11:36:18Z
date_published: 2023-05-01T00:00:00Z
date_updated: 2023-06-01T12:54:45Z
department:
- _id: GradSch
- _id: DaAl
- _id: ChLa
ec_funded: 1
external_id:
arxiv:
- '2207.14200'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://openreview.net/pdf?id=_eTZBs-yedr
month: '05'
oa: 1
oa_version: Preprint
project:
- _id: 268A44D6-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '805223'
name: Elastic Coordination for Scalable Machine Learning
publication: '11th International Conference on Learning Representations '
publication_status: accepted
quality_controlled: '1'
related_material:
record:
- id: '13074'
relation: dissertation_contains
status: public
status: public
title: 'CrAM: A Compression-Aware Minimizer'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2023'
...
---
_id: '13143'
abstract:
- lang: eng
text: "GIMPS and PrimeGrid are large-scale distributed projects dedicated to searching
giant prime numbers, usually of special forms like Mersenne and Proth primes.
The numbers in the current search-space are millions of digits large and the participating
volunteers need to run resource-consuming primality tests. Once a candidate prime
N has been found, the only way for another party to independently verify the primality
of N used to be by repeating the expensive primality test. To avoid the need for
second recomputation of each primality test, these projects have recently adopted
certifying mechanisms that enable efficient verification of performed tests. However,
the mechanisms presently in place only detect benign errors and there is no guarantee
against adversarial behavior: a malicious volunteer can mislead the project to
reject a giant prime as being non-prime.\r\nIn this paper, we propose a practical,
cryptographically-sound mechanism for certifying the non-primality of Proth numbers.
That is, a volunteer can – parallel to running the primality test for N – generate
an efficiently verifiable proof at a little extra cost certifying that N is not
prime. The interactive protocol has statistical soundness and can be made non-interactive
using the Fiat-Shamir heuristic.\r\nOur approach is based on a cryptographic primitive
called Proof of Exponentiation (PoE) which, for a group G, certifies that a tuple
(x,y,T)∈G2×N satisfies x2T=y (Pietrzak, ITCS 2019 and Wesolowski, J. Cryptol.
2020). In particular, we show how to adapt Pietrzak’s PoE at a moderate additional
cost to make it a cryptographically-sound certificate of non-primality."
acknowledgement: 'We are grateful to Pavel Atnashev for clarifying via e-mail several
aspects of the primality tests implementated in the PrimeGrid project. Pavel Hubáček
is supported by the Czech Academy of Sciences (RVO 67985840), the Grant Agency of
the Czech Republic under the grant agreement no. 19-27871X, and by the Charles University
project UNCE/SCI/004. Chethan Kamath is supported by Azrieli International Postdoctoral
Fellowship, ISF grants 484/18 and 1789/19, and ERC StG project SPP: Secrecy Preserving
Proofs.'
alternative_title:
- LNCS
article_processing_charge: No
author:
- first_name: Charlotte
full_name: Hoffmann, Charlotte
id: 0f78d746-dc7d-11ea-9b2f-83f92091afe7
last_name: Hoffmann
- first_name: Pavel
full_name: Hubáček, Pavel
last_name: Hubáček
- first_name: Chethan
full_name: Kamath, Chethan
last_name: Kamath
- first_name: Krzysztof Z
full_name: Pietrzak, Krzysztof Z
id: 3E04A7AA-F248-11E8-B48F-1D18A9856A87
last_name: Pietrzak
orcid: 0000-0002-9139-1654
citation:
ama: 'Hoffmann C, Hubáček P, Kamath C, Pietrzak KZ. Certifying giant nonprimes.
In: Public-Key Cryptography - PKC 2023. Vol 13940. Springer Nature; 2023:530-553.
doi:10.1007/978-3-031-31368-4_19'
apa: 'Hoffmann, C., Hubáček, P., Kamath, C., & Pietrzak, K. Z. (2023). Certifying
giant nonprimes. In Public-Key Cryptography - PKC 2023 (Vol. 13940, pp.
530–553). Atlanta, GA, United States: Springer Nature. https://doi.org/10.1007/978-3-031-31368-4_19'
chicago: Hoffmann, Charlotte, Pavel Hubáček, Chethan Kamath, and Krzysztof Z Pietrzak.
“Certifying Giant Nonprimes.” In Public-Key Cryptography - PKC 2023, 13940:530–53.
Springer Nature, 2023. https://doi.org/10.1007/978-3-031-31368-4_19.
ieee: C. Hoffmann, P. Hubáček, C. Kamath, and K. Z. Pietrzak, “Certifying giant
nonprimes,” in Public-Key Cryptography - PKC 2023, Atlanta, GA, United
States, 2023, vol. 13940, pp. 530–553.
ista: 'Hoffmann C, Hubáček P, Kamath C, Pietrzak KZ. 2023. Certifying giant nonprimes.
Public-Key Cryptography - PKC 2023. PKC: Public-Key Cryptography, LNCS, vol. 13940,
530–553.'
mla: Hoffmann, Charlotte, et al. “Certifying Giant Nonprimes.” Public-Key Cryptography
- PKC 2023, vol. 13940, Springer Nature, 2023, pp. 530–53, doi:10.1007/978-3-031-31368-4_19.
short: C. Hoffmann, P. Hubáček, C. Kamath, K.Z. Pietrzak, in:, Public-Key Cryptography
- PKC 2023, Springer Nature, 2023, pp. 530–553.
conference:
end_date: 2023-05-10
location: Atlanta, GA, United States
name: 'PKC: Public-Key Cryptography'
start_date: 2023-05-07
date_created: 2023-06-18T22:00:47Z
date_published: 2023-05-02T00:00:00Z
date_updated: 2023-06-19T08:03:37Z
day: '02'
department:
- _id: KrPi
doi: 10.1007/978-3-031-31368-4_19
intvolume: ' 13940'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://eprint.iacr.org/2023/238
month: '05'
oa: 1
oa_version: Submitted Version
page: 530-553
publication: Public-Key Cryptography - PKC 2023
publication_identifier:
eissn:
- 1611-3349
isbn:
- '9783031313677'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Certifying giant nonprimes
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13940
year: '2023'
...
---
_id: '13142'
abstract:
- lang: eng
text: Reinforcement learning has received much attention for learning controllers
of deterministic systems. We consider a learner-verifier framework for stochastic
control systems and survey recent methods that formally guarantee a conjunction
of reachability and safety properties. Given a property and a lower bound on the
probability of the property being satisfied, our framework jointly learns a control
policy and a formal certificate to ensure the satisfaction of the property with
a desired probability threshold. Both the control policy and the formal certificate
are continuous functions from states to reals, which are learned as parameterized
neural networks. While in the deterministic case, the certificates are invariant
and barrier functions for safety, or Lyapunov and ranking functions for liveness,
in the stochastic case the certificates are supermartingales. For certificate
verification, we use interval arithmetic abstract interpretation to bound the
expected values of neural network functions.
acknowledgement: This work was supported in part by the ERC-2020-AdG 101020093, ERC
CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation
programme under the Marie Skłodowska-Curie Grant Agreement No. 665385.
alternative_title:
- LNCS
article_processing_charge: No
author:
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
- first_name: Mathias
full_name: Lechner, Mathias
id: 3DC22916-F248-11E8-B48F-1D18A9856A87
last_name: Lechner
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
citation:
ama: 'Chatterjee K, Henzinger TA, Lechner M, Zikelic D. A learner-verifier framework
for neural network controllers and certificates of stochastic systems. In: Tools
and Algorithms for the Construction and Analysis of Systems . Vol 13993. Springer
Nature; 2023:3-25. doi:10.1007/978-3-031-30823-9_1'
apa: 'Chatterjee, K., Henzinger, T. A., Lechner, M., & Zikelic, D. (2023). A
learner-verifier framework for neural network controllers and certificates of
stochastic systems. In Tools and Algorithms for the Construction and Analysis
of Systems (Vol. 13993, pp. 3–25). Paris, France: Springer Nature. https://doi.org/10.1007/978-3-031-30823-9_1'
chicago: Chatterjee, Krishnendu, Thomas A Henzinger, Mathias Lechner, and Dorde
Zikelic. “A Learner-Verifier Framework for Neural Network Controllers and Certificates
of Stochastic Systems.” In Tools and Algorithms for the Construction and Analysis
of Systems , 13993:3–25. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-30823-9_1.
ieee: K. Chatterjee, T. A. Henzinger, M. Lechner, and D. Zikelic, “A learner-verifier
framework for neural network controllers and certificates of stochastic systems,”
in Tools and Algorithms for the Construction and Analysis of Systems ,
Paris, France, 2023, vol. 13993, pp. 3–25.
ista: 'Chatterjee K, Henzinger TA, Lechner M, Zikelic D. 2023. A learner-verifier
framework for neural network controllers and certificates of stochastic systems.
Tools and Algorithms for the Construction and Analysis of Systems . TACAS: Tools
and Algorithms for the Construction and Analysis of Systems, LNCS, vol. 13993,
3–25.'
mla: Chatterjee, Krishnendu, et al. “A Learner-Verifier Framework for Neural Network
Controllers and Certificates of Stochastic Systems.” Tools and Algorithms for
the Construction and Analysis of Systems , vol. 13993, Springer Nature, 2023,
pp. 3–25, doi:10.1007/978-3-031-30823-9_1.
short: K. Chatterjee, T.A. Henzinger, M. Lechner, D. Zikelic, in:, Tools and Algorithms
for the Construction and Analysis of Systems , Springer Nature, 2023, pp. 3–25.
conference:
end_date: 2023-04-27
location: Paris, France
name: 'TACAS: Tools and Algorithms for the Construction and Analysis of Systems'
start_date: 2023-04-22
date_created: 2023-06-18T22:00:47Z
date_published: 2023-04-22T00:00:00Z
date_updated: 2023-06-19T08:30:54Z
day: '22'
ddc:
- '000'
department:
- _id: KrCh
- _id: ToHe
doi: 10.1007/978-3-031-30823-9_1
ec_funded: 1
file:
- access_level: open_access
checksum: 3d8a8bb24d211bc83360dfc2fd744307
content_type: application/pdf
creator: dernst
date_created: 2023-06-19T08:29:30Z
date_updated: 2023-06-19T08:29:30Z
file_id: '13150'
file_name: 2023_LNCS_Chatterjee.pdf
file_size: 528455
relation: main_file
success: 1
file_date_updated: 2023-06-19T08:29:30Z
has_accepted_license: '1'
intvolume: ' 13993'
language:
- iso: eng
license: https://creativecommons.org/licenses/by/4.0/
month: '04'
oa: 1
oa_version: Published Version
page: 3-25
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication: 'Tools and Algorithms for the Construction and Analysis of Systems '
publication_identifier:
eissn:
- 1611-3349
isbn:
- '9783031308222'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: A learner-verifier framework for neural network controllers and certificates
of stochastic systems
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: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13993
year: '2023'
...