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Articles by Peter Eastman

Nutmeg and SPICE: Models and Data for Biomolecular Machine Learning
14 September 2024 by Peter Eastman and others
Chemical Physics, Machine Learning
On the design space between molecular mechanics and machine learning force fields
5 September 2024 by Yuanqing Wang and others
Chemical Physics, Artificial Intelligence
TorchMD-Net 2.0: Fast Neural Network Potentials for Molecular Simulations
23 May 2024 by Raúl Peláez and others at LogoUniversitat Pompeu Fabra
Machine Learning, Biological Physics
OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials
29 November 2023 by Peter Eastman and others at LogoStanford University
Chemical Physics, Machine Learning
NNP/MM: Accelerating molecular dynamics simulations with machine learning potentials and molecular mechanic
28 August 2023 by Raimondas Galvelis and others
Biomolecules, Machine Learning
SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials
23 November 2022 by Peter Eastman and others
Chemical Physics, Machine Learning
Classical Quantum Optimization with Neural Network Quantum States
23 October 2019 by Joseph Gomes and others
Disordered Systems and Neural Networks, Strongly Correlated Electrons
Predicting Gene Expression Between Species with Neural Networks
5 July 2019 by Peter Eastman and Vijay Pande
Genomics
Predicting Toxicity from Gene Expression with Neural Networks
31 January 2019 by Peter Eastman and Vijay Pande
Genomics
Weakly-Supervised Deep Learning of Heat Transport via Physics Informed Loss
21 August 2018 by Rishi Sharma and others
Machine Learning
OpenMM 7: Rapid Development of High Performance Algorithms for Molecular Dynamics
26 July 2017 by P. Eastman and others at LogoStanford University
Biophysics
MSMBuilder: Statistical Models for Biomolecular Dynamics
10 January 2017 by M. Harrigan and others at LogoStanford University
Biophysics