7.7k citations · 8.6k across the 13 of their papers we have counts for
13 papers
Solving the Schrödinger Equation in the Configuration Space with Generative Machine Learning
B. Herzog, B. Casier, S. Lebègue +1
The configuration interaction approach provides a conceptually simple and powerful approach to solve the Schrödinger equation for realistic molecules and materials but is character…
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…
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…
Substrate screening approach for quasiparticle energies of two-dimensional interfaces with lattice mismatch
Chunhao Guo, Junqing Xu, Dario Rocca +1
Two-dimensional (2D) materials are outstanding platforms for exotic physics and emerging applications by forming interfaces. In order to efficiently take into account the substrate…
Self-consistent potential correction for charged periodic systems
Mauricio Chagas da Silva, Michael Lorke, Bálint Aradi +5
Supercell models are often used to calculate the electronic structure of local perturbations from the ideal periodicity in the bulk or on the surface of a crystal or in wires. When…
Bridging molecular dynamics and correlated wave-function methods for accurate finite-temperature properties
Dario Rocca, Anant Dixit, Michael Badawi +3
We introduce the "selPT" perturbative approach, based on ab initio molecular dynamics (AIMD), for computing accurate finite-temperature properties by efficiently using correlated w…