---
_id: '8703'
abstract:
- lang: eng
text: 'Even though Delaunay originally introduced his famous triangulations in the
case of infinite point sets with translational periodicity, a software that computes
such triangulations in the general case is not yet available, to the best of our
knowledge. Combining and generalizing previous work, we present a practical algorithm
for computing such triangulations. The algorithm has been implemented and experiments
show that its performance is as good as the one of the CGAL package, which is
restricted to cubic periodicity. '
alternative_title:
- LIPIcs
article_number: '75'
article_processing_charge: No
author:
- first_name: Georg F
full_name: Osang, Georg F
id: 464B40D6-F248-11E8-B48F-1D18A9856A87
last_name: Osang
orcid: 0000-0002-8882-5116
- first_name: Mael
full_name: Rouxel-Labbé, Mael
last_name: Rouxel-Labbé
- first_name: Monique
full_name: Teillaud, Monique
last_name: Teillaud
citation:
ama: 'Osang GF, Rouxel-Labbé M, Teillaud M. Generalizing CGAL periodic Delaunay
triangulations. In: 28th Annual European Symposium on Algorithms. Vol 173.
Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2020. doi:10.4230/LIPIcs.ESA.2020.75'
apa: 'Osang, G. F., Rouxel-Labbé, M., & Teillaud, M. (2020). Generalizing CGAL
periodic Delaunay triangulations. In 28th Annual European Symposium on Algorithms
(Vol. 173). Virtual, Online; Pisa, Italy: Schloss Dagstuhl - Leibniz-Zentrum für
Informatik. https://doi.org/10.4230/LIPIcs.ESA.2020.75'
chicago: Osang, Georg F, Mael Rouxel-Labbé, and Monique Teillaud. “Generalizing
CGAL Periodic Delaunay Triangulations.” In 28th Annual European Symposium on
Algorithms, Vol. 173. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020.
https://doi.org/10.4230/LIPIcs.ESA.2020.75.
ieee: G. F. Osang, M. Rouxel-Labbé, and M. Teillaud, “Generalizing CGAL periodic
Delaunay triangulations,” in 28th Annual European Symposium on Algorithms,
Virtual, Online; Pisa, Italy, 2020, vol. 173.
ista: 'Osang GF, Rouxel-Labbé M, Teillaud M. 2020. Generalizing CGAL periodic Delaunay
triangulations. 28th Annual European Symposium on Algorithms. ESA: Annual European
Symposium on Algorithms, LIPIcs, vol. 173, 75.'
mla: Osang, Georg F., et al. “Generalizing CGAL Periodic Delaunay Triangulations.”
28th Annual European Symposium on Algorithms, vol. 173, 75, Schloss Dagstuhl
- Leibniz-Zentrum für Informatik, 2020, doi:10.4230/LIPIcs.ESA.2020.75.
short: G.F. Osang, M. Rouxel-Labbé, M. Teillaud, in:, 28th Annual European Symposium
on Algorithms, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2020.
conference:
end_date: 2020-09-09
location: Virtual, Online; Pisa, Italy
name: 'ESA: Annual European Symposium on Algorithms'
start_date: 2020-09-07
date_created: 2020-10-25T23:01:18Z
date_published: 2020-08-26T00:00:00Z
date_updated: 2023-09-07T13:29:00Z
day: '26'
ddc:
- '000'
department:
- _id: HeEd
doi: 10.4230/LIPIcs.ESA.2020.75
ec_funded: 1
file:
- access_level: open_access
checksum: fe0f7c49a99ed870c671b911e10d5496
content_type: application/pdf
creator: cziletti
date_created: 2020-10-27T14:31:52Z
date_updated: 2020-10-27T14:31:52Z
file_id: '8712'
file_name: 2020_LIPIcs_Osang.pdf
file_size: 733291
relation: main_file
success: 1
file_date_updated: 2020-10-27T14:31:52Z
has_accepted_license: '1'
intvolume: ' 173'
language:
- iso: eng
license: https://creativecommons.org/licenses/by/3.0/
month: '08'
oa: 1
oa_version: Published Version
project:
- _id: 266A2E9E-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '788183'
name: Alpha Shape Theory Extended
publication: 28th Annual European Symposium on Algorithms
publication_identifier:
isbn:
- '9783959771627'
issn:
- '18688969'
publication_status: published
publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik
quality_controlled: '1'
related_material:
record:
- id: '9056'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Generalizing CGAL periodic Delaunay triangulations
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/3.0/legalcode
name: Creative Commons Attribution 3.0 Unported (CC BY 3.0)
short: CC BY (3.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 173
year: '2020'
...
---
_id: '8163'
abstract:
- lang: eng
text: Fejes Tóth [3] studied approximations of smooth surfaces in three-space by
piecewise flat triangular meshes with a given number of vertices on the surface
that are optimal with respect to Hausdorff distance. He proves that this Hausdorff
distance decreases inversely proportional with the number of vertices of the approximating
mesh if the surface is convex. He also claims that this Hausdorff distance is
inversely proportional to the square of the number of vertices for a specific
non-convex surface, namely a one-sheeted hyperboloid of revolution bounded by
two congruent circles. We refute this claim, and show that the asymptotic behavior
of the Hausdorff distance is linear, that is the same as for convex surfaces.
acknowledgement: "The authors are greatly indebted to Dror Atariah, Günther Rote and
John Sullivan for discussion and suggestions. The authors also thank Jean-Daniel
Boissonnat, Ramsay Dyer, David de Laat and Rien van de Weijgaert for discussion.
This work has been supported in part by the European Union’s Seventh Framework Programme
for Research of the\r\nEuropean Commission, under FET-Open grant number 255827 (CGL
Computational Geometry Learning) and ERC Grant Agreement number 339025 GUDHI (Algorithmic
Foundations of Geometry Understanding in Higher Dimensions), the European Union’s
Horizon 2020 research and innovation programme under the Marie Sk lodowska-Curie
grant agreement number 754411,and the Austrian Science Fund (FWF): Z00342 N31."
article_processing_charge: No
article_type: original
author:
- first_name: Gert
full_name: Vegter, Gert
last_name: Vegter
- first_name: Mathijs
full_name: Wintraecken, Mathijs
id: 307CFBC8-F248-11E8-B48F-1D18A9856A87
last_name: Wintraecken
orcid: 0000-0002-7472-2220
citation:
ama: Vegter G, Wintraecken M. Refutation of a claim made by Fejes Tóth on the accuracy
of surface meshes. Studia Scientiarum Mathematicarum Hungarica. 2020;57(2):193-199.
doi:10.1556/012.2020.57.2.1454
apa: Vegter, G., & Wintraecken, M. (2020). Refutation of a claim made by Fejes
Tóth on the accuracy of surface meshes. Studia Scientiarum Mathematicarum Hungarica.
Akadémiai Kiadó. https://doi.org/10.1556/012.2020.57.2.1454
chicago: Vegter, Gert, and Mathijs Wintraecken. “Refutation of a Claim Made by Fejes
Tóth on the Accuracy of Surface Meshes.” Studia Scientiarum Mathematicarum
Hungarica. Akadémiai Kiadó, 2020. https://doi.org/10.1556/012.2020.57.2.1454.
ieee: G. Vegter and M. Wintraecken, “Refutation of a claim made by Fejes Tóth on
the accuracy of surface meshes,” Studia Scientiarum Mathematicarum Hungarica,
vol. 57, no. 2. Akadémiai Kiadó, pp. 193–199, 2020.
ista: Vegter G, Wintraecken M. 2020. Refutation of a claim made by Fejes Tóth on
the accuracy of surface meshes. Studia Scientiarum Mathematicarum Hungarica. 57(2),
193–199.
mla: Vegter, Gert, and Mathijs Wintraecken. “Refutation of a Claim Made by Fejes
Tóth on the Accuracy of Surface Meshes.” Studia Scientiarum Mathematicarum
Hungarica, vol. 57, no. 2, Akadémiai Kiadó, 2020, pp. 193–99, doi:10.1556/012.2020.57.2.1454.
short: G. Vegter, M. Wintraecken, Studia Scientiarum Mathematicarum Hungarica 57
(2020) 193–199.
date_created: 2020-07-24T07:09:18Z
date_published: 2020-07-24T00:00:00Z
date_updated: 2023-10-10T13:05:27Z
day: '24'
ddc:
- '510'
department:
- _id: HeEd
doi: 10.1556/012.2020.57.2.1454
ec_funded: 1
external_id:
isi:
- '000570978400005'
file:
- access_level: open_access
content_type: application/pdf
creator: mwintrae
date_created: 2020-07-24T07:09:06Z
date_updated: 2020-07-24T07:09:06Z
file_id: '8164'
file_name: 57-2-05_4214-1454Vegter-Wintraecken_OpenAccess_CC-BY-NC.pdf
file_size: 1476072
relation: main_file
file_date_updated: 2020-07-24T07:09:06Z
has_accepted_license: '1'
intvolume: ' 57'
isi: 1
issue: '2'
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc/4.0/
month: '07'
oa: 1
oa_version: Published Version
page: 193-199
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
- _id: 268116B8-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z00342
name: The Wittgenstein Prize
publication: Studia Scientiarum Mathematicarum Hungarica
publication_identifier:
eissn:
- 1588-2896
issn:
- 0081-6906
publication_status: published
publisher: Akadémiai Kiadó
quality_controlled: '1'
scopus_import: '1'
status: public
title: Refutation of a claim made by Fejes Tóth on the accuracy of surface meshes
tmp:
image: /images/cc_by_nc.png
legal_code_url: https://creativecommons.org/licenses/by-nc/4.0/legalcode
name: Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
short: CC BY-NC (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 57
year: '2020'
...
---
_id: '9157'
abstract:
- lang: eng
text: Representing an atom by a solid sphere in 3-dimensional Euclidean space, we
get the space-filling diagram of a molecule by taking the union. Molecular dynamics
simulates its motion subject to bonds and other forces, including the solvation
free energy. The morphometric approach [12, 17] writes the latter as a linear
combination of weighted versions of the volume, area, mean curvature, and Gaussian
curvature of the space-filling diagram. We give a formula for the derivative of
the weighted mean curvature. Together with the derivatives of the weighted volume
in [7], the weighted area in [3], and the weighted Gaussian curvature [1], this
yields the derivative of the morphometric expression of the solvation free energy.
acknowledgement: "The authors of this paper thank Roland Roth for suggesting the analysis
of the weighted\r\ncurvature derivatives for the purpose of improving molecular
dynamics simulations and for his continued encouragement. They also thank Patrice
Koehl for the implementation of the formulas and for his encouragement and advise
along the road. Finally, they thank two anonymous reviewers for their constructive
criticism.\r\nThis project has received funding from the European Research Council
(ERC) under the European Union’s Horizon 2020 research and innovation programme
(grant agreement No 78818 Alpha). It is also partially supported by the DFG Collaborative
Research Center TRR 109, ‘Discretization in Geometry and Dynamics’, through grant
no. I02979-N35 of the Austrian Science Fund (FWF)."
article_processing_charge: No
article_type: original
author:
- first_name: Arseniy
full_name: Akopyan, Arseniy
id: 430D2C90-F248-11E8-B48F-1D18A9856A87
last_name: Akopyan
orcid: 0000-0002-2548-617X
- first_name: Herbert
full_name: Edelsbrunner, Herbert
id: 3FB178DA-F248-11E8-B48F-1D18A9856A87
last_name: Edelsbrunner
orcid: 0000-0002-9823-6833
citation:
ama: Akopyan A, Edelsbrunner H. The weighted mean curvature derivative of a space-filling
diagram. Computational and Mathematical Biophysics. 2020;8(1):51-67. doi:10.1515/cmb-2020-0100
apa: Akopyan, A., & Edelsbrunner, H. (2020). The weighted mean curvature derivative
of a space-filling diagram. Computational and Mathematical Biophysics.
De Gruyter. https://doi.org/10.1515/cmb-2020-0100
chicago: Akopyan, Arseniy, and Herbert Edelsbrunner. “The Weighted Mean Curvature
Derivative of a Space-Filling Diagram.” Computational and Mathematical Biophysics.
De Gruyter, 2020. https://doi.org/10.1515/cmb-2020-0100.
ieee: A. Akopyan and H. Edelsbrunner, “The weighted mean curvature derivative of
a space-filling diagram,” Computational and Mathematical Biophysics, vol.
8, no. 1. De Gruyter, pp. 51–67, 2020.
ista: Akopyan A, Edelsbrunner H. 2020. The weighted mean curvature derivative of
a space-filling diagram. Computational and Mathematical Biophysics. 8(1), 51–67.
mla: Akopyan, Arseniy, and Herbert Edelsbrunner. “The Weighted Mean Curvature Derivative
of a Space-Filling Diagram.” Computational and Mathematical Biophysics,
vol. 8, no. 1, De Gruyter, 2020, pp. 51–67, doi:10.1515/cmb-2020-0100.
short: A. Akopyan, H. Edelsbrunner, Computational and Mathematical Biophysics 8
(2020) 51–67.
date_created: 2021-02-17T15:13:01Z
date_published: 2020-06-20T00:00:00Z
date_updated: 2023-10-17T12:34:51Z
day: '20'
ddc:
- '510'
department:
- _id: HeEd
doi: 10.1515/cmb-2020-0100
ec_funded: 1
file:
- access_level: open_access
checksum: cea41de9937d07a3b927d71ee8b4e432
content_type: application/pdf
creator: dernst
date_created: 2021-02-19T13:56:24Z
date_updated: 2021-02-19T13:56:24Z
file_id: '9171'
file_name: 2020_CompMathBiophysics_Akopyan2.pdf
file_size: 562359
relation: main_file
success: 1
file_date_updated: 2021-02-19T13:56:24Z
has_accepted_license: '1'
intvolume: ' 8'
issue: '1'
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
page: 51-67
project:
- _id: 266A2E9E-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '788183'
name: Alpha Shape Theory Extended
- _id: 2561EBF4-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: I02979-N35
name: Persistence and stability of geometric complexes
publication: Computational and Mathematical Biophysics
publication_identifier:
issn:
- 2544-7297
publication_status: published
publisher: De Gruyter
quality_controlled: '1'
status: public
title: The weighted mean curvature derivative of a space-filling diagram
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: 8
year: '2020'
...
---
_id: '9156'
abstract:
- lang: eng
text: The morphometric approach [11, 14] writes the solvation free energy as a linear
combination of weighted versions of the volume, area, mean curvature, and Gaussian
curvature of the space-filling diagram. We give a formula for the derivative of
the weighted Gaussian curvature. Together with the derivatives of the weighted
volume in [7], the weighted area in [4], and the weighted mean curvature in [1],
this yields the derivative of the morphometric expression of solvation free energy.
acknowledgement: "The authors of this paper thank Roland Roth for suggesting the analysis
of theweighted\r\ncurvature derivatives for the purpose of improving molecular dynamics
simulations. They also thank Patrice Koehl for the implementation of the formulas
and for his encouragement and advise along the road. Finally, they thank two anonymous
reviewers for their constructive criticism.\r\nThis project has received funding
from the European Research Council (ERC) under the European Union’s Horizon 2020
research and innovation programme (grant agreement No 78818 Alpha). It is also partially
supported by the DFG Collaborative Research Center TRR 109, ‘Discretization in Geometry
and Dynamics’, through grant no. I02979-N35 of the Austrian Science Fund (FWF)."
article_processing_charge: No
article_type: original
author:
- first_name: Arseniy
full_name: Akopyan, Arseniy
id: 430D2C90-F248-11E8-B48F-1D18A9856A87
last_name: Akopyan
orcid: 0000-0002-2548-617X
- first_name: Herbert
full_name: Edelsbrunner, Herbert
id: 3FB178DA-F248-11E8-B48F-1D18A9856A87
last_name: Edelsbrunner
orcid: 0000-0002-9823-6833
citation:
ama: Akopyan A, Edelsbrunner H. The weighted Gaussian curvature derivative of a
space-filling diagram. Computational and Mathematical Biophysics. 2020;8(1):74-88.
doi:10.1515/cmb-2020-0101
apa: Akopyan, A., & Edelsbrunner, H. (2020). The weighted Gaussian curvature
derivative of a space-filling diagram. Computational and Mathematical Biophysics.
De Gruyter. https://doi.org/10.1515/cmb-2020-0101
chicago: Akopyan, Arseniy, and Herbert Edelsbrunner. “The Weighted Gaussian Curvature
Derivative of a Space-Filling Diagram.” Computational and Mathematical Biophysics.
De Gruyter, 2020. https://doi.org/10.1515/cmb-2020-0101.
ieee: A. Akopyan and H. Edelsbrunner, “The weighted Gaussian curvature derivative
of a space-filling diagram,” Computational and Mathematical Biophysics,
vol. 8, no. 1. De Gruyter, pp. 74–88, 2020.
ista: Akopyan A, Edelsbrunner H. 2020. The weighted Gaussian curvature derivative
of a space-filling diagram. Computational and Mathematical Biophysics. 8(1), 74–88.
mla: Akopyan, Arseniy, and Herbert Edelsbrunner. “The Weighted Gaussian Curvature
Derivative of a Space-Filling Diagram.” Computational and Mathematical Biophysics,
vol. 8, no. 1, De Gruyter, 2020, pp. 74–88, doi:10.1515/cmb-2020-0101.
short: A. Akopyan, H. Edelsbrunner, Computational and Mathematical Biophysics 8
(2020) 74–88.
date_created: 2021-02-17T15:12:44Z
date_published: 2020-07-21T00:00:00Z
date_updated: 2023-10-17T12:35:10Z
day: '21'
ddc:
- '510'
department:
- _id: HeEd
doi: 10.1515/cmb-2020-0101
ec_funded: 1
external_id:
arxiv:
- '1908.06777'
file:
- access_level: open_access
checksum: ca43a7440834eab6bbea29c59b56ef3a
content_type: application/pdf
creator: dernst
date_created: 2021-02-19T13:33:19Z
date_updated: 2021-02-19T13:33:19Z
file_id: '9170'
file_name: 2020_CompMathBiophysics_Akopyan.pdf
file_size: 707452
relation: main_file
success: 1
file_date_updated: 2021-02-19T13:33:19Z
has_accepted_license: '1'
intvolume: ' 8'
issue: '1'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
page: 74-88
project:
- _id: 266A2E9E-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '788183'
name: Alpha Shape Theory Extended
- _id: 2561EBF4-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: I02979-N35
name: Persistence and stability of geometric complexes
publication: Computational and Mathematical Biophysics
publication_identifier:
issn:
- 2544-7297
publication_status: published
publisher: De Gruyter
quality_controlled: '1'
status: public
title: The weighted Gaussian curvature derivative of a space-filling diagram
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: 8
year: '2020'
...
---
_id: '15064'
abstract:
- lang: eng
text: We call a continuous self-map that reveals itself through a discrete set of
point-value pairs a sampled dynamical system. Capturing the available information
with chain maps on Delaunay complexes, we use persistent homology to quantify
the evidence of recurrent behavior. We establish a sampling theorem to recover
the eigenspaces of the endomorphism on homology induced by the self-map. Using
a combinatorial gradient flow arising from the discrete Morse theory for Čech
and Delaunay complexes, we construct a chain map to transform the problem from
the natural but expensive Čech complexes to the computationally efficient Delaunay
triangulations. The fast chain map algorithm has applications beyond dynamical
systems.
acknowledgement: This research has been supported by the DFG Collaborative Research
Center SFB/TRR 109 “Discretization in Geometry and Dynamics”, by Polish MNiSzW Grant
No. 2621/7.PR/12/2013/2, by the Polish National Science Center under Maestro Grant
No. 2014/14/A/ST1/00453 and Grant No. DEC-2013/09/N/ST6/02995. Open Access funding
provided by Projekt DEAL.
article_processing_charge: Yes (via OA deal)
article_type: original
author:
- first_name: U.
full_name: Bauer, U.
last_name: Bauer
- first_name: Herbert
full_name: Edelsbrunner, Herbert
id: 3FB178DA-F248-11E8-B48F-1D18A9856A87
last_name: Edelsbrunner
orcid: 0000-0002-9823-6833
- first_name: Grzegorz
full_name: Jablonski, Grzegorz
id: 4483EF78-F248-11E8-B48F-1D18A9856A87
last_name: Jablonski
orcid: 0000-0002-3536-9866
- first_name: M.
full_name: Mrozek, M.
last_name: Mrozek
citation:
ama: Bauer U, Edelsbrunner H, Jablonski G, Mrozek M. Čech-Delaunay gradient flow
and homology inference for self-maps. Journal of Applied and Computational
Topology. 2020;4(4):455-480. doi:10.1007/s41468-020-00058-8
apa: Bauer, U., Edelsbrunner, H., Jablonski, G., & Mrozek, M. (2020). Čech-Delaunay
gradient flow and homology inference for self-maps. Journal of Applied and
Computational Topology. Springer Nature. https://doi.org/10.1007/s41468-020-00058-8
chicago: Bauer, U., Herbert Edelsbrunner, Grzegorz Jablonski, and M. Mrozek. “Čech-Delaunay
Gradient Flow and Homology Inference for Self-Maps.” Journal of Applied and
Computational Topology. Springer Nature, 2020. https://doi.org/10.1007/s41468-020-00058-8.
ieee: U. Bauer, H. Edelsbrunner, G. Jablonski, and M. Mrozek, “Čech-Delaunay gradient
flow and homology inference for self-maps,” Journal of Applied and Computational
Topology, vol. 4, no. 4. Springer Nature, pp. 455–480, 2020.
ista: Bauer U, Edelsbrunner H, Jablonski G, Mrozek M. 2020. Čech-Delaunay gradient
flow and homology inference for self-maps. Journal of Applied and Computational
Topology. 4(4), 455–480.
mla: Bauer, U., et al. “Čech-Delaunay Gradient Flow and Homology Inference for Self-Maps.”
Journal of Applied and Computational Topology, vol. 4, no. 4, Springer
Nature, 2020, pp. 455–80, doi:10.1007/s41468-020-00058-8.
short: U. Bauer, H. Edelsbrunner, G. Jablonski, M. Mrozek, Journal of Applied and
Computational Topology 4 (2020) 455–480.
date_created: 2024-03-04T10:47:49Z
date_published: 2020-12-01T00:00:00Z
date_updated: 2024-03-04T10:54:04Z
day: '01'
ddc:
- '500'
department:
- _id: HeEd
doi: 10.1007/s41468-020-00058-8
file:
- access_level: open_access
checksum: eed1168b6e66cd55272c19bb7fca8a1c
content_type: application/pdf
creator: dernst
date_created: 2024-03-04T10:52:42Z
date_updated: 2024-03-04T10:52:42Z
file_id: '15065'
file_name: 2020_JourApplCompTopology_Bauer.pdf
file_size: 851190
relation: main_file
success: 1
file_date_updated: 2024-03-04T10:52:42Z
has_accepted_license: '1'
intvolume: ' 4'
issue: '4'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
page: 455-480
publication: Journal of Applied and Computational Topology
publication_identifier:
eissn:
- 2367-1734
issn:
- 2367-1726
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Čech-Delaunay gradient flow and homology inference for self-maps
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: 4
year: '2020'
...