55 citations · 129 across the 18 of their papers we have counts for
4 papers · 1 filter
Learning Equivariant Non-Local Electron Density Functionals
Nicholas Gao, Eike Eberhard, Stephan Günnemann
The accuracy of density functional theory hinges on the approximation of non-local contributions to the exchange-correlation (XC) functional. To date, machine-learned and human-des…
Lift Your Molecules: Molecular Graph Generation in Latent Euclidean Space
Mohamed Amine Ketata, Nicholas Gao, Johanna Sommer +2
We introduce a new framework for molecular graph generation with 3D molecular generative models. Our Synthetic Coordinate Embedding (SyCo) framework maps molecular graphs to Euclid…
Neural Pfaffians: Solving Many Many-Electron Schrödinger Equations
Nicholas Gao, Stephan Günnemann
Neural wave functions accomplished unprecedented accuracies in approximating the ground state of many-electron systems, though at a high computational cost. Recent works proposed a…
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…