4 citations · 4 across the 2 of their papers we have counts for
2 papers
cond-mat.mtrl-sci2021
Assessing the Accuracy of Machine Learning Thermodynamic Perturbation Theory: Density Functional Theory and Beyond
Basile Herzog, Mauricio Chagas da Silva, Bastien Casier +5
Machine learning thermodynamic perturbation theory (MLPT) is a promising approach to compute finite temperature properties when the goal is to compare several different levels of a…
physics.chem-ph2020★ 4 cited
Hybrid localized graph kernel for machine learning energy-related properties of molecules and solids
Bastien Casier, Mauricio Chagas da Silva, Michael Badawi +4
Nowadays, the coupling of electronic structure and machine learning techniques serves as a powerful tool to predict chemical and physical properties of a broad range of systems. Wi…