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Max Veit
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Predicting molecular dipole moments by combining atomic partial charges and atomic dipoles
M Veit, DM Wilkins, Y Yang, RA DiStasio, M Ceriotti
The Journal of Chemical Physics 153 (2), 2020
892020
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
882022
Equation of state of fluid methane from first principles with machine learning potentials
M Veit, SK Jain, S Bonakala, I Rudra, D Hohl, G Csányi
Journal of chemical theory and computation 15 (4), 2574-2586, 2019
562019
Efficient implementation of atom-density representations
F Musil, M Veit, A Goscinski, G Fraux, MJ Willatt, M Stricker, T Junge, ...
The Journal of Chemical Physics 154 (11), 2021
482021
Multi-scale electrolyte transport simulations for lithium ion batteries
F Hanke, N Modrow, RLC Akkermans, I Korotkin, FC Mocanu, VA Neufeld, ...
Journal of The Electrochemical Society 167 (1), 013522, 2019
192019
Thermodynamics and dielectric response of BaTiO3 by data-driven modeling
L Gigli, M Veit, M Kotiuga, G Pizzi, N Marzari, M Ceriotti
npj Computational Materials 8 (1), 209, 2022
182022
LIBRASCAL
F Musil, M Veit, T Junge, M Stricker, A Goscinki, G Fraux, M Ceriotti
GitHub, https://github. com/cosmo-epfl/librascal, 2018
52018
Eigenfunction Decomposition of Reactor Perturbations & Transitions Using MCNP Monte Carlo
C Josey, MD Veit
Los Alamos National Lab.(LANL), Los Alamos, NM (United States), 2013
52013
Bulk methane models and simulation parameters
M Veit
12018
Locality of forces in molecular systems
M Veit
University of Cambridge, 2015
12015
Incorporating explicit electrostatic interactions in machine learning potentials
M Veit, M Caro
Bulletin of the American Physical Society, 2024
2024
Dielectric response of BaTiO3 from an integrated machine learning model
M Veit, L Gigli, M Kotiuga, G Pizzi, N Marzari, M Ceriotti
APS March Meeting Abstracts 2022, N69. 008, 2022
2022
Machine learning the molecular dipole moment with atomic partial charges and atomic dipoles
M Veit, D Wilkins, Y Yang, RA DiStasio Jr., M Ceriotti
Bulletin of the American Physical Society, 2021
2021
Representative trajectory data supporting" Multiscale Electrolyte Transport Simulations for Lithium Ion Batteries"
F Hanke, N Modrow, RLC Akkermans, I Korotkin, FC Mocanu, VA Neufeld, ...
2020
Research data supporting" Designing a machine learning potential for molecular simulation of liquid alkanes"
M Veit
2019
Designing a machine learning potential for molecular simulation of liquid alkanes
M Veit
University of Cambridge, 2018
2018
Stochastic Simulation of Genetic Regulatory Networks with Delayed Reactions
M Veit
2014
Boosting feed efficiency and reducing emissions: the influence of phytogenic additives.
A Mader, M Veit
Kraftfutter 93 (7/8), 12-14, 2010
2010
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 Affiliated authors Anelli, Andrea
E Baldi, B Cheng, S Chong, S De, EA Engel, G Fraux, P Gasparotto, ...
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Articles 1–20