7 citations · 10 across the 3 of their papers we have counts for
3 papers
quant-ph2024
On Representing Electronic Wave Functions with Sign Equivariant Neural Networks
Nicholas Gao, Stephan Günnemann
Recent neural networks demonstrated impressively accurate approximations of electronic ground-state wave functions. Such neural networks typically consist of a permutation-equivari…
cs.LG2023★ 7 cited
Ewald-based Long-Range Message Passing for Molecular Graphs
Arthur Kosmala, Johannes Gasteiger, Nicholas Gao +1
Neural architectures that learn potential energy surfaces from molecular data have undergone fast improvement in recent years. A key driver of this success is the Message Passing N…
cs.LG2023★ 3 cited
Generalizing Neural Wave Functions
Nicholas Gao, Stephan Günnemann
Recent neural network-based wave functions have achieved state-of-the-art accuracies in modeling ab-initio ground-state potential energy surface. However, these networks can only s…