Informing Geometric Deep Learning with Electronic Interactions to
Accelerate Quantum Chemistry

Informing Geometric Deep Learning with Electronic Interactions to Accelerate Quantum Chemistry

31 May 2021

Anders S. Christensen

Matthew Welborn

Anima Anandkumar

Thomas F. Miller

Papers citing "Informing Geometric Deep Learning with Electronic Interactions to Accelerate Quantum Chemistry"

11 / 11 papers shown

Title
ELECTRA: A Cartesian Network for 3D Charge Density Prediction with Floating Orbitals Jonas Elsborg Luca Thiede Alán Aspuru-Guzik Tejs Vegge Arghya Bhowmik 54 0 0 11 Mar 2025
A Recipe for Charge Density Prediction Xiang Fu Andrew S. Rosen Kyle Bystrom Rui Wang Albert Musaelian Boris Kozinsky Tess E. Smidt Tommi Jaakkola 71 6 0 29 May 2024
FeNNol: an Efficient and Flexible Library for Building Force-field-enhanced Neural Network Potentials Thomas Plé Olivier Adjoua Louis Lagardère Jean‐Philip Piquemal 63 8 0 02 May 2024
High Accuracy Uncertainty-Aware Interatomic Force Modeling with Equivariant Bayesian Neural Networks Tim Rensmeyer Benjamin Craig D. Kramer Oliver Niggemann BDL 54 3 0 05 Apr 2023
Fast Uncertainty Estimates in Deep Learning Interatomic Potentials Albert J. W. Zhu Simon L. Batzner Albert Musaelian Boris Kozinsky 27 45 0 17 Nov 2022
Graph Neural Networks for Molecules Yuyang Wang Zijie Li A. Farimani GNN AI4CE 52 23 0 12 Sep 2022
A smooth basis for atomistic machine learning Filippo Bigi Kevin K. Huguenin-Dumittan Michele Ceriotti D. Manolopoulos 35 6 0 05 Sep 2022
Molecular Dipole Moment Learning via Rotationally Equivariant Gaussian Process Regression with Derivatives in Molecular-orbital-based Machine Learning Jiace Sun Lixue Cheng Thomas F. Miller 40 2 0 31 May 2022
Equivariant graph neural networks for fast electron density estimation of molecules, liquids, and solids Peter Bjørn Jørgensen Arghya Bhowmik 18 36 0 01 Dec 2021
Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges M. Bronstein Joan Bruna Taco S. Cohen Petar Velivcković GNN 180 1,128 0 27 Apr 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 259 1,253 0 08 Jan 2021