EGraFFBench: Evaluation of Equivariant Graph Neural Network Force Fields
for Atomistic Simulations

EGraFFBench: Evaluation of Equivariant Graph Neural Network Force Fields for Atomistic Simulations

3 October 2023

Utkarsh Pratiush

Matthieu Micoulaut

N. M. A. Krishnan

Papers citing "EGraFFBench: Evaluation of Equivariant Graph Neural Network Force Fields for Atomistic Simulations"

9 / 9 papers shown

Title
CrystalFramer: Rethinking the Role of Frames for SE(3)-Invariant Crystal Structure Modeling Yusei Ito Tatsunori Taniai Ryo Igarashi Yoshitaka Ushiku K. Ono 57 0 0 04 Mar 2025
Improving the Stability of GNN Force Field Models by Reducing Feature Correlation Y. Zeng Wenlong He Ihor Vasyltsov Jiaxin Wei Ying Zhang Lin Chen Yuehua Dai 31 0 0 18 Feb 2025
Deconstructing equivariant representations in molecular systems Kin Long Kelvin Lee Mikhail Galkin Santiago Miret 17 1 0 10 Oct 2024
A Recipe for Charge Density Prediction Xiang Fu Andrew S. Rosen Kyle Bystrom Rui Wang Albert Musaelian Boris Kozinsky Tess E. Smidt Tommi Jaakkola 31 5 0 29 May 2024
TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations Raúl P. Peláez Guillem Simeon Raimondas Galvelis Antonio Mirarchi Peter K. Eastman Stefan Doerr Philipp Thölke T. Markland Gianni de Fabritiis AI4CE 17 12 0 27 Feb 2024
Predicting and Interpreting Energy Barriers of Metallic Glasses with Graph Neural Networks Haoyu Li Shichang Zhang Longwen Tang Mathieu Bauchy Yizhou Sun AI4CE 29 0 0 08 Dec 2023
TensorNet: Cartesian Tensor Representations for Efficient Learning of Molecular Potentials Guillem Simeon Gianni de Fabritiis 11 43 0 10 Jun 2023
Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs Yi-Lun Liao Tess E. Smidt 73 142 0 23 Jun 2022
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