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1

First-principles spectroscopy of aqueous interfaces using m..:

Kapil, Venkat ; Kovács, Dávid Péter ; Csányi, Gábor.
Faraday Discussions. 249 (2024) - p. 50-68 , 2024

Link: https://doi.org/10.1039/..

2

Hyperactive learning for data-driven interatomic potentials:

van der Oord, Cas ; Sachs, Matthias ; Kovács, Dávid Péter..
npj Computational Materials. 9 (2023) 1 - p. , 2023

Link: https://doi.org/10.1038/..

3

Evaluation of the MACE force field architecture: From medic..:

Kovács, Dávid Péter ; Batatia, Ilyes ; Arany, Eszter Sára.
The Journal of Chemical Physics. 159 (2023) 4 - p. , 2023

Link: https://doi.org/10.1063/..

4

Linear Atomic Cluster Expansion Force Fields for Organic Mo..:

Kovács, Dávid Péter ; Oord, Cas van der ; Kucera, Jiri...
Journal of Chemical Theory and Computation. 17 (2021) 12 - p. 7696-7711 , 2021

Link: https://doi.org/10.1021/..

5

Quantitative interpretation explains machine learning model..:

Kovács, Dávid Péter ; McCorkindale, William ; Lee, Alpha A.
Nature Communications. 12 (2021) 1 - p. , 2021

Link: https://doi.org/10.1038/..

6

MACE-OFF23: Transferable Machine Learning Force Fields for ..:

Kovács, Dávid Péter ; Moore, J. Harry ; Browning, Nicholas J...
http://arxiv.org/abs/2312.15211. , 2023

Link: http://arxiv.org/abs/231..

7

Evaluation of the MACE Force Field Architecture: from Medic..:

Kovacs, David Peter ; Batatia, Ilyes ; Arany, Eszter Sara.
http://arxiv.org/abs/2305.14247. , 2023

Link: http://arxiv.org/abs/230..

8

Hyperactive learning for data-driven interatomic potentials:

van der Oord, Cas ; Csanyi, Gabor ; Sachs, Matthias..
https://www.repository.cam.ac.uk/handle/1810/354363. , 2023

Link: https://www.repository.c..

9

MACE: Higher Order Equivariant Message Passing Neural Netwo..:

Batatia, Ilyes ; Kovács, Dávid Péter ; Simm, Gregor N. C..
http://arxiv.org/abs/2206.07697. , 2022

Link: http://arxiv.org/abs/220..

10

The Design Space of E(3)-Equivariant Atom-Centered Interato..:

Batatia, Ilyes ; Batzner, Simon ; Kovács, Dávid Péter...
http://arxiv.org/abs/2205.06643. , 2022

Link: http://arxiv.org/abs/220..

11

Hyperactive Learning (HAL) for Data-Driven Interatomic Pote..:

van der Oord, Cas ; Sachs, Matthias ; Kovács, Dávid Péter..
http://arxiv.org/abs/2210.04225. , 2022

Link: http://arxiv.org/abs/221..

12

Quantitative interpretation explains machine learning model..:

Kovács, Dávid Péter ; McCorkindale, William ; Lee, Alpha A
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7966799/. , 2021

Link: http://www.ncbi.nlm.nih...

13

Quantitative interpretation explains machine learning model..:

Kovács, Dávid Péter ; McCorkindale, William ; Lee, Alpha A
doi:10.17863/CAM.65964. , 2021

Link: https://doi.org/10.17863..

14

Laparoscopic resection of ganglioneuroma from the hepatoduo..:

Felföldi, Tamás ; Varga, Zsolt ; Kolozsi, Péter..
International Journal of Surgery Case Reports. 112 (2023) - p. 108914 , 2023

Link: https://doi.org/10.1016/..

15

Metal artefact reduction for accurate tumour delineation in..:

Kovacs, David Gergely ; Rechner, Laura A. ; Appelt, Ane L....
Radiotherapy and Oncology. 126 (2018) 3 - p. 479-486 , 2018

Link: https://doi.org/10.1016/..

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