A Perspective on Deep Learning for Molecular Modeling and Simulations

25 April 2020

Papers citing "A Perspective on Deep Learning for Molecular Modeling and Simulations"

20 / 20 papers shown

Title
Machine Learning of coarse-grained Molecular Dynamics Force Fields Jiang Wang Simon Olsson C. Wehmeyer Adria Pérez Nicholas E. Charron Gianni De Fabritiis Frank Noe C. Clementi AI4CE 38 401 0 04 Dec 2018
Solving Statistical Mechanics Using Variational Autoregressive Networks Dian Wu Lei Wang Pan Zhang 56 183 0 27 Sep 2018
Relational inductive biases, deep learning, and graph networks Peter W. Battaglia Jessica B. Hamrick V. Bapst Alvaro Sanchez-Gonzalez V. Zambaldi ... Pushmeet Kohli M. Botvinick Oriol Vinyals Yujia Li Razvan Pascanu AI4CE NAI 527 3,101 0 04 Jun 2018
Parallel WaveNet: Fast High-Fidelity Speech Synthesis Aaron van den Oord Yazhe Li Igor Babuschkin Karen Simonyan Oriol Vinyals ... Alex Graves Helen King T. Walters Dan Belov Demis Hassabis 177 858 0 28 Nov 2017
SchNet: A continuous-filter convolutional neural network for modeling quantum interactions Kristof T. Schütt Pieter-Jan Kindermans Huziel Enoc Sauceda Felix Stefan Chmiela A. Tkatchenko K. Müller 127 1,069 0 26 Jun 2017
Curiosity-driven Exploration by Self-supervised Prediction Deepak Pathak Pulkit Agrawal Alexei A. Efros Trevor Darrell LRM SSL 106 2,423 0 15 May 2017
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks Chelsea Finn Pieter Abbeel Sergey Levine OOD 781 11,793 0 09 Mar 2017
Deep Bayesian Active Learning with Image Data Y. Gal Riashat Islam Zoubin Ghahramani BDL UQCV 64 1,717 0 08 Mar 2017
Interaction Networks for Learning about Objects, Relations and Physics Peter W. Battaglia Razvan Pascanu Matthew Lai Danilo Jimenez Rezende Koray Kavukcuoglu AI4CE OCL PINN GNN 494 1,405 0 01 Dec 2016
Learning to learn by gradient descent by gradient descent Marcin Andrychowicz Misha Denil Sergio Gomez Colmenarejo Matthew W. Hoffman David Pfau Tom Schaul Brendan Shillingford Nando de Freitas 96 2,000 0 14 Jun 2016
Matching Networks for One Shot Learning Oriol Vinyals Charles Blundell Timothy Lillicrap Koray Kavukcuoglu Daan Wierstra VLM 325 7,299 0 13 Jun 2016
Asynchronous Methods for Deep Reinforcement Learning Volodymyr Mnih Adria Puigdomenech Badia M. Berk Mirza Alex Graves Timothy Lillicrap Tim Harley David Silver Koray Kavukcuoglu 170 8,805 0 04 Feb 2016
Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) Djork-Arné Clevert Thomas Unterthiner Sepp Hochreiter 250 5,502 0 23 Nov 2015
Convolutional Networks on Graphs for Learning Molecular Fingerprints David Duvenaud D. Maclaurin J. Aguilera-Iparraguirre Rafael Gómez-Bombarelli Timothy D. Hirzel Alán Aspuru-Guzik Ryan P. Adams GNN 177 3,337 0 30 Sep 2015
Continuous control with deep reinforcement learning Timothy Lillicrap Jonathan J. Hunt Alexander Pritzel N. Heess Tom Erez Yuval Tassa David Silver Daan Wierstra 260 13,174 0 09 Sep 2015
Probabilistic Backpropagation for Scalable Learning of Bayesian Neural Networks José Miguel Hernández-Lobato Ryan P. Adams UQCV BDL 92 940 0 18 Feb 2015
Deep Learning in Neural Networks: An Overview Jürgen Schmidhuber HAI 202 16,311 0 30 Apr 2014
Spectral Networks and Locally Connected Networks on Graphs Joan Bruna Wojciech Zaremba Arthur Szlam Yann LeCun GNN 174 4,856 0 21 Dec 2013
Auto-Encoding Variational Bayes Diederik P. Kingma Max Welling BDL 397 16,962 0 20 Dec 2013
Fast and Accurate Modeling of Molecular Atomization Energies with Machine Learning M. Rupp A. Tkatchenko K. Müller O. A. von Lilienfeld AI4CE 140 1,581 0 12 Sep 2011