| Roadmap on machine learning in electronic structure HJ Kulik, T Hammerschmidt, J Schmidt, S Botti, MAL Marques, M Boley, ... Electronic Structure 4 (2), 023004, 2022 | 102 | 2022 |
| Recursive evaluation and iterative contraction of N-body equivariant features J Nigam, S Pozdnyakov, M Ceriotti The Journal of chemical physics 153 (12), 2020 | 71 | 2020 |
| Multi-scale approach for the prediction of atomic scale properties A Grisafi, J Nigam, M Ceriotti Chemical science 12 (6), 2078-2090, 2021 | 46 | 2021 |
| Equivariant representations for molecular Hamiltonians and N-center atomic-scale properties J Nigam, MJ Willatt, M Ceriotti The Journal of Chemical Physics 156 (1), 2022 | 45 | 2022 |
| Unified theory of atom-centered representations and message-passing machine-learning schemes J Nigam, S Pozdnyakov, G Fraux, M Ceriotti The Journal of Chemical Physics 156 (20), 2022 | 25 | 2022 |
| Optimal radial basis for density-based atomic representations A Goscinski, F Musil, S Pozdnyakov, J Nigam, M Ceriotti The Journal of Chemical Physics 155 (10), 2021 | 22 | 2021 |
| Completeness of atomic structure representations J Nigam, SN Pozdnyakov, KK Huguenin-Dumittan, M Ceriotti APL Machine Learning 2 (1), 2024 | 7 | 2024 |
| Roadmap on machine learning in electronic structure Electron H Kulik, T Hammerschmidt, J Schmidt, S Botti, MAL Marques, M Boley, ... Struct 4, 023004, 2022 | 5 | 2022 |
| Characterization of Test Mass Scattering: LIGO SURF Report J Nigam, G Venugopalan, J Eichholz https://dcc.ligo.org/LIGO-T1700283/public, 2017 | 2* | 2017 |
| Unified theory of atom-centered representations and graph convolutional machine-learning schemes J Nigam, G Fraux, M Ceriotti arXiv e-prints, arXiv: 2202.01566, 2022 | 1 | 2022 |
| Expanding Density-Correlation Machine Learning Representations for Anisotropic Coarse-Grained Particles AY Lin, KK Huguenin-Dumittan, YC Cho, J Nigam, RK Cersonsky arXiv preprint arXiv:2403.19039, 2024 | | 2024 |
| Completeness of representations in atomistic machine learning J Nigam, M Ceriotti, S Pozdnyakov, K Huguenin-Dumittan Bulletin of the American Physical Society, 2024 | | 2024 |
| Anisotropic Machine Learning Representations for Multiscale Systems A Lin, K Huguenin-Dumittan, J Nigam, YC Cho, R Cersonsky Bulletin of the American Physical Society, 2024 | | 2024 |
| Electronic Excited States from Physically Constrained Machine Learning E Cignoni, D Suman, J Nigam, L Cupellini, B Mennucci, M Ceriotti ACS Central Science 10 (3), 637-648, 2024 | | 2024 |
| Unifying atom-centered descriptions and message-passing machine learning schemes J Nigam, M Ceriotti APS March Meeting Abstracts 2023, D17. 009, 2023 | | 2023 |
| Section 2.6-Integrated machine learning models: electronic structure accuracy beyond local potentials M Veit, A Grisafi, J Nigam, M Ceriotti Roadmap on Machine Learning in Electronic Structure, 47, 0 | | |
| Group ID U12743 A Anelli, E Baldi, B Mahmoud, F Chiheb Bigi, M Ceriotti, R Cersonsky, ... | | |
Michele CeriottiAssociate Professor at EPFL, Institute of MaterialsVerified email at epfl.ch
