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Andrea Grisafi
Andrea Grisafi
Post-doctoral researcher, Sorbonne Université, Paris
Verified email at sorbonne-universite.fr
Title
Cited by
Cited by
Year
Physics-inspired structural representations for molecules and materials
F Musil, A Grisafi, AP Bartók, C Ortner, G Csányi, M Ceriotti
Chemical Reviews 121 (16), 9759-9815, 2021
3792021
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
2712018
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
2472018
Accurate molecular polarizabilities with coupled cluster theory and machine learning
DM Wilkins, A Grisafi, Y Yang, KU Lao, RA DiStasio Jr, M Ceriotti
Proceedings of the National Academy of Sciences 116 (9), 3401-3406, 2019
1792019
Incorporating long-range physics in atomic-scale machine learning
A Grisafi, M Ceriotti
The Journal of chemical physics 151 (20), 2019
1552019
Electron density learning of non-covalent systems
A Fabrizio, A Grisafi, B Meyer, M Ceriotti, C Corminboeuf
Chemical science 10 (41), 9424-9432, 2019
1362019
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
1092022
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
682019
Multi-scale approach for the prediction of atomic scale properties
A Grisafi, J Nigam, M Ceriotti
Chemical science 12 (6), 2078-2090, 2021
502021
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
402017
Quantum mechanical static dipole polarizabilities in the QM7b and AlphaML showcase databases
Y Yang, KU Lao, DM Wilkins, A Grisafi, M Ceriotti, RA DiStasio Jr
Scientific data 6 (1), 152, 2019
372019
Learning electron densities in the condensed phase
AM Lewis, A Grisafi, M Ceriotti, M Rossi
Journal of chemical theory and computation 17 (11), 7203-7214, 2021
322021
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
172019
Electronic-structure properties from atom-centered predictions of the electron density
A Grisafi, AM Lewis, M Rossi, M Ceriotti
Journal of Chemical Theory and Computation 19 (14), 4451-4460, 2022
142022
Machine learning in chemistry: data-driven algorithms, learning systems, and predictions
A Grisafi, D Wilkins, M Willatt, M Ceriotti
American Chemical Society, 2019
132019
Learning (from) the Electron Density: Transferability, Conformational and Chemical Diversity
A Fabrizio, K Briling, A Grisafi, C Corminboeuf
Chimia 74 (4), 232-232, 2020
112020
Predicting the charge density response in metal electrodes
A Grisafi, A Bussy, M Salanne, R Vuilleumier
Physical Review Materials 7 (12), 125403, 2023
72023
Effect of a temperature gradient on the screening properties of ionic fluids
A Grisafi, F Grasselli
Physical Review Materials 7 (4), 045803, 2023
32023
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
32016
Accelerating QM/MM simulations of electrochemical interfaces through machine learning of electronic charge densities
A Grisafi, M Salanne
arXiv preprint arXiv:2405.07370, 2024
2024
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