| MACE: Higher order equivariant message passing neural networks for fast and accurate force fields I Batatia, DP Kovács, GNC Simm, C Ortner, G Csányi Advances in Neural Information Processing Systems (NeurIPS) 2022, 2022 | 558 | 2022 |
| Validation of the CoGEF method as a predictive tool for polymer mechanochemistry IM Klein, CC Husic, DP Kovács, NJ Choquette, MJ Robb Journal of the American Chemical Society 142 (38), 16364-16381, 2020 | 171 | 2020 |
| A foundation model for atomistic materials chemistry I Batatia, P Benner, Y Chiang, AM Elena, DP Kovács, J Riebesell, ... arXiv preprint arXiv:2401.00096, 2023 | 151 | 2023 |
| Linear atomic cluster expansion force fields for organic molecules: beyond rmse DP Kovács, C Oord, J Kucera, AEA Allen, DJ Cole, C Ortner, G Csányi Journal of chemical theory and computation 17 (12), 7696-7711, 2021 | 127 | 2021 |
| The design space of E (3)-equivariant atom-centred interatomic potentials I Batatia, S Batzner, DP Kovács, A Musaelian, GNC Simm, R Drautz, ... Nature Machine Intelligence, 1-12, 2025 | 125* | 2025 |
| Quantitative interpretation explains machine learning models for chemical reaction prediction and uncovers bias DP Kovács, W McCorkindale, AA Lee Nature Communications 12 (1), 1-9, 2021 | 78 | 2021 |
| Evaluation of the MACE force field architecture: From medicinal chemistry to materials science G Kovács, Dávid Péter and Batatia, Ilyes and Arany, Eszter Sára and Csányi The Journal of Chemical Physics 159 (4), 044118, 2023 | 74 | 2023 |
| Hyperactive learning for data-driven interatomic potentials C van der Oord, M Sachs, DP Kovács, C Ortner, G Csányi npj Computational Materials 9 (1), 168, 2023 | 61 | 2023 |
| MACE-OFF23: Transferable machine learning force fields for organic molecules DP Kovács, JH Moore, NJ Browning, I Batatia, JT Horton, V Kapil, WC Witt, ... arXiv preprint arXiv:2312.15211, 2023 | 53 | 2023 |
| Tensor-reduced atomic density representations JP Darby, DP Kovács, I Batatia, MA Caro, GLW Hart, C Ortner, G Csányi Physical Review Letters 131 (2), 028001, 2023 | 36 | 2023 |
| First-principles spectroscopy of aqueous interfaces using machine-learned electronic and quantum nuclear effects V Kapil, DP Kovács, G Csányi, A Michaelides Faraday Discussions 249, 50-68, 2024 | 29 | 2024 |
| The Design Space of E (3)-Equivariant Atom-Centered Interatomic Potentials. 2022 I Batatia, S Batzner, DP Kovács, A Musaelian, GNC Simm, R Drautz, ... URL https://arxiv. org/abs/2205.06643 5, 0 | 23 | |
| MACE-OFF23: Transferable Machine Learning Force Fields for Organic Molecules (2023) DP Kovács, JH Moore, NJ Browning, I Batatia, JT Horton, V Kapil, WC Witt, ... arXiv preprint arXiv:2312.15211, 0 | 20 | |
| A foundation model for atomistic materials chemistry, 2024 I Batatia, P Benner, Y Chiang, AM Elena, DP Kovács, J Riebesell, ... arXiv preprint arXiv:2401.00096, 0 | 18 | |
| Zero Shot Molecular Generation via Similarity Kernels R Elijošius, F Zills, I Batatia, SW Norwood, DP Kovács, C Holm, G Csányi arXiv preprint arXiv:2402.08708, 2024 | 6 | 2024 |
| Machine Learning Force Fields for Molecular Chemistry D Kovács | | 2024 |
| Research data supporting" MACE-OFF23" H Moore, DP Kovacs, NJ Browning, I Batatia, JT Horton, V Kapil, W Witt, ... | | 2024 |
