TorchMD: A deep learning framework for molecular simulations

TorchMD: A deep learning framework for molecular simulations

22 December 2020

Maciej Majewski

Andreas Krämer

Frank Noe

Gianni De Fabritiis

Papers citing "TorchMD: A deep learning framework for molecular simulations"

16 / 16 papers shown

Title
Surrogate modeling of Cellular-Potts Agent-Based Models as a segmentation task using the U-Net neural network architecture Tien Comlekoglu J. Q. Toledo-Marín Tina Comlekoglu Douglas W. DeSimone Shayn M. Peirce Geoffrey C. Fox J. Glazier 67 1 0 01 May 2025
Equivariant Masked Position Prediction for Efficient Molecular Representation Junyi An C. Qu Yun-Fei Shi XinHao Liu Qianwei Tang Fenglei Cao Yuan Qi 40 0 0 12 Feb 2025
chemtrain: Learning Deep Potential Models via Automatic Differentiation and Statistical Physics Paul Fuchs Stephan Thaler Sebastien Röcken Julija Zavadlav DiffM 82 6 0 28 Aug 2024
Molecule Graph Networks with Many-body Equivariant Interactions Zetian Mao Jiawen Li Chen Liang Diptesh Das Masato Sumita Koji Tsuda Kelin Xia Koji Tsuda 35 1 0 19 Jun 2024
Machine Learning Coarse-Grained Potentials of Protein Thermodynamics Maciej Majewski Adriana Pérez Philipp Thölke Stefan Doerr N. Charron T. Giorgino B. Husic C. Clementi Frank Noé Gianni De Fabritiis AI4CE 21 70 0 14 Dec 2022
SchNetPack 2.0: A neural network toolbox for atomistic machine learning Kristof T. Schütt Stefaan S. P. Hessmann Niklas W. A. Gebauer Jonas Lederer M. Gastegger 25 59 0 11 Dec 2022
Forces are not Enough: Benchmark and Critical Evaluation for Machine Learning Force Fields with Molecular Simulations Xiang Fu Zhenghao Wu Wujie Wang T. Xie S. Keten Rafael Gómez-Bombarelli Tommi Jaakkola 32 138 0 13 Oct 2022
Learning Pair Potentials using Differentiable Simulations Wujie Wang Zhenghao Wu Rafael Gómez-Bombarelli 25 23 0 16 Sep 2022
Building Robust Machine Learning Models for Small Chemical Science Data: The Case of Shear Viscosity Nikhil V. S. Avula S. K. Veesam Sudarshan Behera S. Balasubramanian 24 8 0 23 Aug 2022
Automatic Identification of Chemical Moieties Jonas Lederer M. Gastegger Kristof T. Schütt Michael C. Kampffmeyer Klaus-Robert Muller Oliver T. Unke 21 5 0 30 Mar 2022
Differentiable Matrix Elements with MadJax Lukas Heinrich Michael Kagan 30 19 0 28 Feb 2022
TorchMD-NET: Equivariant Transformers for Neural Network based Molecular Potentials Philipp Thölke Gianni De Fabritiis AI4CE 34 186 0 05 Feb 2022
Graph Neural Networks Accelerated Molecular Dynamics Zijie Li Kazem Meidani Prakarsh Yadav A. Farimani GNN AI4CE 21 53 0 06 Dec 2021
Learning neural network potentials from experimental data via Differentiable Trajectory Reweighting Stephan Thaler Julija Zavadlav 22 66 0 02 Jun 2021
Coupling streaming AI and HPC ensembles to achieve 100-1000x faster biomolecular simulations Alexander Brace I. Yakushin Heng Ma Anda Trifan T. Munson Ian Foster A. Ramanathan Hyungro Lee Matteo Turilli S. Jha AI4CE 27 19 0 10 Apr 2021
Coarse Graining Molecular Dynamics with Graph Neural Networks B. Husic N. Charron Dominik Lemm Jiang Wang Adria Pérez ... Yaoyi Chen Simon Olsson Gianni De Fabritiis Frank Noé C. Clementi AI4CE 40 158 0 22 Jul 2020