| Symmetry-adapted machine learning for tensorial properties of atomistic systems A Grisafi, DM Wilkins, G Csányi, M Ceriotti Physical review letters 120 (3), 036002, 2018 | 136 | 2018 |
| Transferable machine-learning model of the electron density A Grisafi, A Fabrizio, B Meyer, DM Wilkins, C Corminboeuf, M Ceriotti ACS central science 5 (1), 57-64, 2018 | 85 | 2018 |
| Accurate molecular polarizabilities with coupled cluster theory and machine learning DM Wilkins, A Grisafi, Y Yang, KU Lao, RA DiStasio, M Ceriotti Proceedings of the National Academy of Sciences 116 (9), 3401-3406, 2019 | 57 | 2019 |
| Electron density learning of non-covalent systems A Fabrizio, A Grisafi, B Meyer, M Ceriotti, C Corminboeuf Chemical science 10 (41), 9424-9432, 2019 | 35 | 2019 |
| Incorporating long-range physics in atomic-scale machine learning A Grisafi, M Ceriotti The Journal of chemical physics 151 (20), 204105, 2019 | 26 | 2019 |
| Solvent fluctuations and nuclear quantum effects modulate the molecular hyperpolarizability of water C Liang, G Tocci, DM Wilkins, A Grisafi, S Roke, M Ceriotti Physical Review B 96 (4), 041407, 2017 | 23 | 2017 |
| Using Gaussian process regression to simulate the vibrational Raman spectra of molecular crystals N Raimbault, A Grisafi, M Ceriotti, M Rossi New Journal of Physics 21 (10), 105001, 2019 | 14 | 2019 |
| Atomic-scale representation and statistical learning of tensorial properties A Grisafi, DM Wilkins, MJ Willatt, M Ceriotti Machine Learning in Chemistry: Data-Driven Algorithms, Learning Systems, and …, 2019 | 6 | 2019 |
| Learning (from) the Electron Density: Transferability, Conformational and Chemical Diversity A Fabrizio, K Briling, A Grisafi, C Corminboeuf CHIMIA International Journal for Chemistry 74 (4), 232-236, 2020 | 3 | 2020 |
| Quantum mechanical static dipole polarizabilities in the QM7b and AlphaML showcase databases Y Yang, KU Lao, DM Wilkins, A Grisafi, M Ceriotti, RA DiStasio Scientific data 6 (1), 1-10, 2019 | 3 | 2019 |
| Localized Polycentric Orbital Basis Set for Quantum Monte Carlo Calculations Derived from the Decomposition of Kohn-Sham Optimized Orbitals C Amovilli, FM Floris, A Grisafi Computation 4 (1), 10, 2016 | 3 | 2016 |
| Multi-scale approach for the prediction of atomic scale properties A Grisafi, J Nigam, M Ceriotti arXiv preprint arXiv:2008.12122, 2020 | 2 | 2020 |
| Solute-solvent interactions and solvation free energy: a density functional investigation A GRISAFI | | 2016 |
| Physics-inspired structural representations for molecules and materials F Musil, A Grisafi, AP Bartók, C Ortner, G Csányi, M Ceriotti arXiv preprint arXiv:2101.04673, 0 | | |
Michele CeriottiAssociate Professor at EPFL, Institute of MaterialsVerified email at epfl.ch
