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Poltavsky, Igor
45
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Online (45)
Mediatypes
Articles (Online) (20)
Bookchapter (Online) (1)
OpenAccess-fulltext (24)
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1
Explainable chemical artificial intelligence from accurate ..:
Gallegos, Miguel
;
Vassilev-Galindo, Valentin
;
Poltavsky, Igor
..
Nature Communications. 15 (2024) 1 - p. , 2024
Link:
https://doi.org/10.1038/..
?
2
Efficient interatomic descriptors for accurate machine lear..:
Kabylda, Adil
;
Vassilev-Galindo, Valentin
;
Chmiela, Stefan
..
Nature Communications. 14 (2023) 1 - p. , 2023
Link:
https://doi.org/10.1038/..
?
3
Modeling molecular ensembles with gradient-domain machine l..:
Maldonado, Alex M.
;
Poltavsky, Igor
;
Vassilev-Galindo, Valentin
..
Digital Discovery. 2 (2023) 3 - p. 871-880 , 2023
Link:
https://doi.org/10.1039/..
?
4
Author Correction: Efficient interatomic descriptors for ac..:
Kabylda, Adil
;
Vassilev-Galindo, Valentin
;
Chmiela, Stefan
..
Nature Communications. 14 (2023) 1 - p. , 2023
Link:
https://doi.org/10.1038/..
?
5
Force Field Analysis Software and Tools (FFAST): Assessing ..:
Fonseca, Gregory
;
Poltavsky, Igor
;
Tkatchenko, Alexandre
Journal of Chemical Theory and Computation. 19 (2023) 23 - p. 8706-8717 , 2023
Link:
https://doi.org/10.1021/..
?
6
Improving molecular force fields across configurational spa..:
Fonseca, Gregory
;
Poltavsky, Igor
;
Vassilev-Galindo, Valentin
.
The Journal of Chemical Physics. 154 (2021) 12 - p. , 2021
Link:
https://doi.org/10.1063/..
?
7
Machine Learning Force Fields:
Unke, Oliver T.
;
Chmiela, Stefan
;
Sauceda, Huziel E.
...
Chemical Reviews. 121 (2021) 16 - p. 10142-10186 , 2021
Link:
https://doi.org/10.1021/..
?
8
Challenges for machine learning force fields in reproducing..:
Vassilev-Galindo, Valentin
;
Fonseca, Gregory
;
Poltavsky, Igor
.
The Journal of Chemical Physics. 154 (2021) 9 - p. , 2021
Link:
https://doi.org/10.1063/..
?
9
Machine Learning Force Fields: Recent Advances and Remainin..:
Poltavsky, Igor
;
Tkatchenko, Alexandre
The Journal of Physical Chemistry Letters. 12 (2021) 28 - p. 6551-6564 , 2021
Link:
https://doi.org/10.1021/..
?
10
Construction of Machine Learned Force Fields with Quantum C..:
, In:
Machine Learning Meets Quantum Physics; Lecture Notes in Physics
,
Sauceda, Huziel E.
;
Chmiela, Stefan
;
Poltavsky, Igor
.. - p. 277-307 , 2020
Link:
https://doi.org/10.1007/..
?
11
Accurate Description of Nuclear Quantum Effects with High-O..:
Poltavsky, Igor
;
Kapil, Venkat
;
Ceriotti, Michele
..
Journal of Chemical Theory and Computation. 16 (2020) 2 - p. 1128-1135 , 2020
Link:
https://doi.org/10.1021/..
?
12
i-PI 2.0: A universal force engine for advanced molecular s..:
Kapil, Venkat
;
Rossi, Mariana
;
Marsalek, Ondrej
...
Computer Physics Communications. 236 (2019) - p. 214-223 , 2019
Link:
https://doi.org/10.1016/..
?
13
sGDML: Constructing accurate and data efficient molecular f..:
Chmiela, Stefan
;
Sauceda, Huziel E.
;
Poltavsky, Igor
..
Computer Physics Communications. 240 (2019) - p. 38-45 , 2019
Link:
https://doi.org/10.1016/..
?
14
Molecular force fields with gradient-domain machine learnin..:
Sauceda, Huziel E.
;
Chmiela, Stefan
;
Poltavsky, Igor
..
The Journal of Chemical Physics. 150 (2019) 11 - p. , 2019
Link:
https://doi.org/10.1063/..
?
15
Stability of functionalized platform molecules on Au(111):
Jasper-Tönnies, Torben
;
Poltavsky, Igor
;
Ulrich, Sandra
...
The Journal of Chemical Physics. 149 (2018) 24 - p. , 2018
Link:
https://doi.org/10.1063/..
1-15