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Learning Equivariant Non-Local Electron Density Functionals

10 October 2024

Nicholas Gao

Eike Eberhard

Stephan Günnemann

Author Contacts:

n.gao@tum.de e.eberhard@tum.de s.guennemann@tum.de

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Papers citing "Learning Equivariant Non-Local Electron Density Functionals"

22 / 22 papers shown

Title
Highly Accurate Real-space Electron Densities with Neural Networks Lixue Cheng P. Szabó Zeno Schätzle Derk Kooi Jonas Köhler Klaas J. H. Giesbertz Frank Noé J. Hermann Paola Gori-Giorgi Adam Foster 80 5 0 02 Sep 2024
Neural Pfaffians: Solving Many Many-Electron Schrödinger Equations Nicholas Gao Stephan Günnemann 66 5 0 23 May 2024
On Representing Electronic Wave Functions with Sign Equivariant Neural Networks Nicholas Gao Stephan Günnemann 55 3 0 08 Mar 2024
Overcoming the Barrier of Orbital-Free Density Functional Theory for Molecular Systems Using Deep Learning He Zhang Siyuan Liu Jiacheng You Chang-Shu Liu Shuxin Zheng Ziheng Lu Tong Wang Nanning Zheng Jia Zhang 46 20 0 28 Sep 2023
KineticNet: Deep learning a transferable kinetic energy functional for orbital-free density functional theory Roman Remme Tobias Kaczun Maximilian Scheurer A. Dreuw Fred Hamprecht 61 11 0 08 May 2023
Ewald-based Long-Range Message Passing for Molecular Graphs Arthur Kosmala Johannes Gasteiger Nicholas Gao Stephan Günnemann 113 30 0 08 Mar 2023
Generalizing Neural Wave Functions Nicholas Gao Stephan Günnemann 37 24 0 08 Feb 2023
Reducing SO(3) Convolutions to SO(2) for Efficient Equivariant GNNs Saro Passaro C. L. Zitnick 3DPC 73 90 0 07 Feb 2023
MACE: Higher Order Equivariant Message Passing Neural Networks for Fast and Accurate Force Fields Ilyes Batatia D. P. Kovács G. Simm Christoph Ortner Gábor Csányi 87 485 0 15 Jun 2022
Sampling-free Inference for Ab-Initio Potential Energy Surface Networks Nicholas Gao Stephan Günnemann DiffM 68 20 0 30 May 2022
So3krates: Equivariant attention for interactions on arbitrary length-scales in molecular systems J. Frank Oliver T. Unke Klaus-Robert Muller 51 43 0 28 May 2022
Directional Message Passing on Molecular Graphs via Synthetic Coordinates Johannes Klicpera Chandan Yeshwanth Stephan Günnemann 49 38 0 08 Nov 2021
Ab-Initio Potential Energy Surfaces by Pairing GNNs with Neural Wave Functions Nicholas Gao Stephan Günnemann 63 40 0 11 Oct 2021
GemNet: Universal Directional Graph Neural Networks for Molecules Johannes Klicpera Florian Becker Stephan Günnemann AI4CE 97 459 0 02 Jun 2021
Equivariant message passing for the prediction of tensorial properties and molecular spectra Kristof T. Schütt Oliver T. Unke M. Gastegger 110 534 0 05 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 300 1,298 0 08 Jan 2021
Machine Learning Force Fields Oliver T. Unke Stefan Chmiela H. E. Sauceda M. Gastegger I. Poltavsky Kristof T. Schütt A. Tkatchenko K. Müller AI4CE 109 913 0 14 Oct 2020
Kohn-Sham equations as regularizer: building prior knowledge into machine-learned physics Li Li Stephan Hoyer Ryan Pederson Ruoxi Sun E. D. Cubuk Patrick F. Riley K. Burke AI4CE 69 122 0 17 Sep 2020
Tensor field networks: Rotation- and translation-equivariant neural networks for 3D point clouds Nathaniel Thomas Tess E. Smidt S. Kearnes Lusann Yang Li Li Kai Kohlhoff Patrick F. Riley 3DPC 95 973 0 22 Feb 2018
SchNet: A continuous-filter convolutional neural network for modeling quantum interactions Kristof T. Schütt Pieter-Jan Kindermans Huziel Enoc Sauceda Felix Stefan Chmiela A. Tkatchenko K. Müller 155 1,076 0 26 Jun 2017
Gaussian Error Linear Units (GELUs) Dan Hendrycks Kevin Gimpel 172 5,011 0 27 Jun 2016
Finding Density Functionals with Machine Learning John C. Snyder M. Rupp K. Hansen K. Müller K. Burke 110 476 0 22 Dec 2011