Forces are not Enough: Benchmark and Critical Evaluation for Machine
Learning Force Fields with Molecular Simulations

Forces are not Enough: Benchmark and Critical Evaluation for Machine Learning Force Fields with Molecular Simulations

13 October 2022

Rafael Gómez-Bombarelli

Papers citing "Forces are not Enough: Benchmark and Critical Evaluation for Machine Learning Force Fields with Molecular Simulations"

13 / 13 papers shown

Title
Quantifying Robustness: A Benchmarking Framework for Deep Learning Forecasting in Cyber-Physical Systems Alexander Windmann Henrik S. Steude Daniel Boschmann Oliver Niggemann OOD AI4TS 31 0 0 04 Apr 2025
Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models Luis Barroso-Luque Muhammed Shuaibi Xiang Fu Brandon M. Wood Misko Dzamba Meng Gao Ammar Rizvi C. L. Zitnick Zachary W. Ulissi AI4CE PINN 24 16 0 16 Oct 2024
Physics-Informed Weakly Supervised Learning for Interatomic Potentials Makoto Takamoto Viktor Zaverkin Mathias Niepert AI4CE 52 0 0 23 Jul 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 39 5 0 29 May 2024
EGraFFBench: Evaluation of Equivariant Graph Neural Network Force Fields for Atomistic Simulations Vaibhav Bihani Utkarsh Pratiush Sajid Mannan Tao Du Zhimin Chen Santiago Miret Matthieu Micoulaut M. Smedskjaer Sayan Ranu N. M. A. Krishnan 19 19 0 03 Oct 2023
Matbench Discovery -- A framework to evaluate machine learning crystal stability predictions Janosh Riebesell Rhys E. A. Goodall Philipp Benner Chiang Yuan Bowen Deng A. Lee Anubhav Jain Kristin A. Persson OOD 19 33 0 28 Aug 2023
Scaling the leading accuracy of deep equivariant models to biomolecular simulations of realistic size Albert Musaelian A. Johansson Simon L. Batzner Boris Kozinsky 19 48 0 20 Apr 2023
SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials Peter K. Eastman P. Behara David L. Dotson Raimondas Galvelis John E. Herr ... J. Chodera Benjamin P. Pritchard Yuanqing Wang Gianni de Fabritiis T. Markland 24 105 0 21 Sep 2022
Equiformer: Equivariant Graph Attention Transformer for 3D Atomistic Graphs Yi-Lun Liao Tess E. Smidt 73 211 0 23 Jun 2022
SpookyNet: Learning Force Fields with Electronic Degrees of Freedom and Nonlocal Effects Oliver T. Unke Stefan Chmiela M. Gastegger Kristof T. Schütt H. E. Sauceda K. Müller 142 242 0 01 May 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 188 1,218 0 08 Jan 2021
The Open Catalyst 2020 (OC20) Dataset and Community Challenges L. Chanussot Abhishek Das Siddharth Goyal Thibaut Lavril Muhammed Shuaibi ... Brandon M. Wood Junwoong Yoon Devi Parikh C. L. Zitnick Zachary W. Ulissi 213 498 0 20 Oct 2020
Differentiable Molecular Simulations for Control and Learning Wujie Wang Simon Axelrod Rafael Gómez-Bombarelli AI4CE 88 49 0 27 Feb 2020