6 citations · 14 across the 6 of their papers we have counts for
3 papers · 1 filter
Transferable Neural Wavefunctions for Solids
Leon Gerard, Michael Scherbela, Halvard Sutterud +2
Deep-Learning-based Variational Monte Carlo (DL-VMC) has recently emerged as a highly accurate approach for finding approximate solutions to the many-electron Schrödinger equation.…
Towards a Foundation Model for Neural Network Wavefunctions
Michael Scherbela, Leon Gerard, Philipp Grohs
Deep neural networks have become a highly accurate and powerful wavefunction ansatz in combination with variational Monte Carlo methods for solving the electronic Schrödinger equat…
Solving the electronic Schrödinger equation for multiple nuclear geometries with weight-sharing deep neural networks
Michael Scherbela, Rafael Reisenhofer, Leon Gerard +2
Accurate numerical solutions for the Schrödinger equation are of utmost importance in quantum chemistry. However, the computational cost of current high-accuracy methods scales poo…