Sampling-free Inference for Ab-Initio Potential Energy Surface Networks

Sampling-free Inference for Ab-Initio Potential Energy Surface Networks

30 May 2022

Stephan Günnemann

Papers citing "Sampling-free Inference for Ab-Initio Potential Energy Surface Networks"

7 / 7 papers shown

Title
Learning Equivariant Non-Local Electron Density Functionals Nicholas Gao Eike Eberhard Stephan Günnemann 26 1 0 10 Oct 2024
Variational Monte Carlo on a Budget -- Fine-tuning pre-trained Neural Wavefunctions Michael Scherbela Leon Gerard Philipp Grohs 25 5 0 15 Jul 2023
Gold-standard solutions to the Schrödinger equation using deep learning: How much physics do we need? Leon Gerard Michael Scherbela P. Marquetand Philipp Grohs AI4CE 29 34 0 19 May 2022
Explicitly antisymmetrized neural network layers for variational Monte Carlo simulation Jeffmin Lin Gil Goldshlager Lin Lin 32 22 0 07 Dec 2021
High-Performance Large-Scale Image Recognition Without Normalization Andrew Brock Soham De Samuel L. Smith Karen Simonyan VLM 220 450 0 11 Feb 2021
E(3)-Equivariant Graph Neural Networks for Data-Efficient and Accurate Interatomic Potentials Simon L. Batzner Albert Musaelian Lixin Sun Mario Geiger J. Mailoa M. Kornbluth N. Molinari Tess E. Smidt Boris Kozinsky 183 1,218 0 08 Jan 2021
Deep neural network solution of the electronic Schrödinger equation J. Hermann Zeno Schätzle Frank Noé 133 444 0 16 Sep 2019