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Machine Learning of coarse-grained Molecular Dynamics Force Fields

4 December 2018

Frank Noe

Papers citing "Machine Learning of coarse-grained Molecular Dynamics Force Fields"

23 / 73 papers shown

Title
TorchMD: A deep learning framework for molecular simulations Stefan Doerr Maciej Majewski Adria Pérez Andreas Krämer C. Clementi Frank Noe T. Giorgino Gianni De Fabritiis AI4CE 145 173 0 22 Dec 2020
Artificial intelligence techniques for integrative structural biology of intrinsically disordered proteins A. Ramanathan Henglong Ma Akash Parvatikar C. Chennubhotla AI4CE 55 40 0 01 Dec 2020
Machine Learning Force Fields Oliver T. Unke Stefan Chmiela H. E. Sauceda M. Gastegger I. Poltavsky Kristof T. Schütt A. Tkatchenko K. Müller AI4CE 133 935 0 14 Oct 2020
Machine Learning in Nano-Scale Biomedical Engineering Alexandros-Apostolos A. Boulogeorgos Stylianos E. Trevlakis Sotiris A. Tegos V. Papanikolaou G. Karagiannidis AI4CE 34 30 0 05 Aug 2020
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 123 162 0 22 Jul 2020
Deep Learning in Protein Structural Modeling and Design Wenhao Gao S. Mahajan Jeremias Sulam Jeffrey J. Gray 84 161 0 16 Jul 2020
Discovering Symbolic Models from Deep Learning with Inductive Biases M. Cranmer Alvaro Sanchez-Gonzalez Peter W. Battaglia Rui Xu Kyle Cranmer D. Spergel S. Ho AI4CE 96 483 0 19 Jun 2020
Sparse Symplectically Integrated Neural Networks Daniel M. DiPietro S. Xiong Bo Zhu 88 31 0 10 Jun 2020
Ensemble Learning of Coarse-Grained Molecular Dynamics Force Fields with a Kernel Approach Jiang Wang Stefan Chmiela K. Müller Frank Noè C. Clementi 138 46 0 04 May 2020
A Perspective on Deep Learning for Molecular Modeling and Simulations Jun Zhang Yao-Kun Lei Zhen Zhang Junhan Chang Maodong Li Xu Han Lijiang Yang Yue Yang Y. Gao AI4CE 108 8 0 25 Apr 2020
Solving Newton's Equations of Motion with Large Timesteps using Recurrent Neural Networks based Operators J. Kadupitiya Geoffrey C. Fox V. Jadhao AI4CE 70 22 0 12 Apr 2020
Autonomous discovery in the chemical sciences part I: Progress Connor W. Coley Natalie S. Eyke K. Jensen 71 218 0 30 Mar 2020
Differentiable Molecular Simulations for Control and Learning Wujie Wang Simon Axelrod Rafael Gómez-Bombarelli AI4CE 194 49 0 27 Feb 2020
Machine learning for protein folding and dynamics Frank Noé Gianni De Fabritiis C. Clementi AI4CE 111 137 0 22 Nov 2019
Machine learning for molecular simulation Frank Noé A. Tkatchenko K. Müller C. Clementi AI4CE 80 667 0 07 Nov 2019
Learning Everywhere: A Taxonomy for the Integration of Machine Learning and Simulations Geoffrey C. Fox S. Jha AI4CE 72 13 0 29 Sep 2019
Data-driven approximation of the Koopman generator: Model reduction, system identification, and control Stefan Klus Feliks Nuske Sebastian Peitz Jan-Hendrik Niemann C. Clementi Christof Schütte 113 230 0 23 Sep 2019
Understanding ML driven HPC: Applications and Infrastructure Geoffrey C. Fox S. Jha 57 13 0 05 Sep 2019
Generative Models for Automatic Chemical Design Daniel Schwalbe-Koda Rafael Gómez-Bombarelli MedIm AI4CE 87 81 0 02 Jul 2019
Hamiltonian Neural Networks S. Greydanus Misko Dzamba J. Yosinski PINN AI4CE 141 900 0 04 Jun 2019
Learning Everywhere: Pervasive Machine Learning for Effective High-Performance Computation Geoffrey C. Fox J. Glazier J. Kadupitiya V. Jadhao Minje Kim ... Madhav Marathe Abhijin Adiga Jiangzhuo Chen O. Beckstein S. Jha 59 53 0 27 Feb 2019
Machine Learning for Molecular Dynamics on Long Timescales Frank Noé AI4CE 77 32 0 18 Dec 2018
Coarse-Graining Auto-Encoders for Molecular Dynamics Wujie Wang Rafael Gómez-Bombarelli AI4CE 70 167 0 06 Dec 2018