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Šípka, Martin
63
results:
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Online (63)
Mediatypes
Articles (Online) (10)
Bookchapter (Online) (1)
OpenAccess-fulltext (52)
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english (39)
Sorted by: Relevance
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?
1
A reactive neural network framework for water-loaded acidic..:
Erlebach, Andreas
;
Šípka, Martin
;
Saha, Indranil
...
Nature Communications. 15 (2024) 1 - p. , 2024
Link:
https://doi.org/10.1038/..
?
2
Direct Poisson neural networks: learning non-symplectic mec..:
Šípka, Martin
;
Pavelka, Michal
;
Esen, Oğul
.
Journal of Physics A: Mathematical and Theoretical. 56 (2023) 49 - p. 495201 , 2023
Link:
https://doi.org/10.1088/..
?
3
Constructing Collective Variables Using Invariant Learned R..:
Šípka, Martin
;
Erlebach, Andreas
;
Grajciar, Lukáš
Journal of Chemical Theory and Computation. 19 (2023) 3 - p. 887-901 , 2023
Link:
https://doi.org/10.1021/..
?
4
Learning Physics from Data: A Thermodynamic Interpretation:
, In:
Springer Proceedings in Mathematics & Statistics; Geometric Structures of Statistical Physics, Information Geometry, and Learning
,
Chinesta, Francisco
;
Cueto, Elías
;
Grmela, Miroslav
... - p. 276-297 , 2021
Link:
https://doi.org/10.1007/..
?
5
Differentiable Simulations for Enhanced Sampling of Rare Ev..:
Šípka, Martin
;
Dietschreit, Johannes C. B
;
Grajciar, Lukáš
.
http://arxiv.org/abs/2301.03480. , 2023
Link:
http://arxiv.org/abs/230..
?
6
A reactive neural network framework for water-loaded acidic..:
Erlebach, Andreas
;
Šípka, Martin
;
Saha, Indranil
...
http://arxiv.org/abs/2307.00911. , 2023
Link:
http://arxiv.org/abs/230..
?
7
Direct Poisson neural networks: learning non-symplectic mec..:
Šípka, Martin
;
Pavelka, Michal
;
Esen, Oğul
.
https://publications.polymtl.ca/56705/1/2023_Sipka_Direct_poisson_neural_networks_learning.pdf. , 2023
Link:
https://publications.pol..
?
8
Supplementary data (CC BY 4.0): A reactive neural network f..:
Erlebach, Andreas
;
Šípka, Martin
;
Saha, Indranil
...
arxiv:arXiv:2307.00911. , 2023
Link:
https://zenodo.org/recor..
?
9
Direct Poisson neural networks: Learning non-symplectic mec..:
Šípka, Martin
;
Pavelka, Michal
;
Esen, Oğul
.
http://arxiv.org/abs/2305.05540. , 2023
Link:
http://arxiv.org/abs/230..
?
10
Understanding chemical reactions via variational autoencode..:
Šípka, Martin
;
Erlebach, Andreas
;
Grajciar, Lukáš
http://arxiv.org/abs/2203.08097. , 2022
Link:
http://arxiv.org/abs/220..
?
11
On compatibility of the natural configuration framework wit..:
Pelech, Petr
;
Tůma, Karel
;
Pavelka, Michal
..
ISSN:2198-5855. , 2021
Link:
https://oa.tib.eu/renate..
?
12
On compatibility of the natural configuration framework wit..:
Pelech, Petr
;
Tůma, Karel
;
Pavelka, Michal
..
https://doi.org/10.20347/WIAS.PREPRINT.2856. , 2021
Link:
https://doi.org/10.20347..
?
13
Learning the GENERIC evolution:
Šípka, Martin
;
Pavelka, Michal
http://arxiv.org/abs/2109.12659. , 2021
Link:
http://arxiv.org/abs/210..
?
14
On compatibility of the Natural configuration framework wit..:
Pelech, Petr
;
Tuma, Karel
;
Pavelka, Michal
..
http://arxiv.org/abs/2010.06903. , 2020
Link:
http://arxiv.org/abs/201..
?
15
Modeling of anisotropic viscoelastic fluids ; Modelování an..:
Šípka, Martin
http://hdl.handle.net/20.500.11956/116637. , 2020
Link:
https://hdl.handle.net/2..
1-15