Uncertainty quantification of molecular property prediction using Bayesian neural network models

19 November 2018

Papers citing "Uncertainty quantification of molecular property prediction using Bayesian neural network models"

24 / 24 papers shown

Title
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation Jiaxuan You Bowen Liu Rex Ying Vijay S. Pande J. Leskovec GNN 267 895 0 07 Jun 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 479 3,101 0 04 Jun 2018
MolGAN: An implicit generative model for small molecular graphs Nicola De Cao Thomas Kipf GNN GAN 126 917 0 30 May 2018
PotentialNet for Molecular Property Prediction Evan N. Feinberg Debnil Sur Zhenqin Wu B. Husic Huanghao Mai Yang Li Saisai Sun Jianyi Yang Bharath Ramsundar Vijay S. Pande 45 361 0 12 Mar 2018
Learning Deep Generative Models of Graphs Yujia Li Oriol Vinyals Chris Dyer Razvan Pascanu Peter W. Battaglia GNN AI4CE 142 659 0 08 Mar 2018
Junction Tree Variational Autoencoder for Molecular Graph Generation Wengong Jin Regina Barzilay Tommi Jaakkola 303 1,358 0 12 Feb 2018
DeepDTA: Deep Drug-Target Binding Affinity Prediction Hakime Öztürk E. Olmez Arzucan Özgür 73 1,063 0 30 Jan 2018
Graph Attention Networks Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Lio Yoshua Bengio GNN 361 19,991 0 30 Oct 2017
Learning to Plan Chemical Syntheses Marwin H. S. Segler Mike Preuss M. Waller 66 1,364 0 14 Aug 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
Objective-Reinforced Generative Adversarial Networks (ORGAN) for Sequence Generation Models G. L. Guimaraes Benjamín Sánchez-Lengeling Carlos Outeiral Pedro Luis Cunha Farias Alán Aspuru-Guzik GAN 69 523 0 30 May 2017
Concrete Dropout Y. Gal Jiri Hron Alex Kendall BDL UQCV 139 587 0 22 May 2017
Neural Message Passing for Quantum Chemistry Justin Gilmer S. Schoenholz Patrick F. Riley Oriol Vinyals George E. Dahl 345 7,388 0 04 Apr 2017
Atomic Convolutional Networks for Predicting Protein-Ligand Binding Affinity Joseph Gomes Bharath Ramsundar Evan N. Feinberg Vijay S. Pande 44 192 0 30 Mar 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 301 4,667 0 15 Mar 2017
Multiplicative Normalizing Flows for Variational Bayesian Neural Networks Christos Louizos Max Welling BDL 131 456 0 06 Mar 2017
Grammar Variational Autoencoder Matt J. Kusner Brooks Paige José Miguel Hernández-Lobato BDL DRL 71 838 0 06 Mar 2017
Automatic chemical design using a data-driven continuous representation of molecules Rafael Gómez-Bombarelli Jennifer N. Wei David Duvenaud José Miguel Hernández-Lobato Benjamín Sánchez-Lengeling Dennis Sheberla J. Aguilera-Iparraguirre Timothy D. Hirzel Ryan P. Adams Alán Aspuru-Guzik 3DV 137 2,911 0 07 Oct 2016
Semi-Supervised Classification with Graph Convolutional Networks Thomas Kipf Max Welling GNN SSL 501 28,901 0 09 Sep 2016
Neural networks for the prediction organic chemistry reactions Jennifer N. Wei David Duvenaud Alán Aspuru-Guzik 35 353 0 22 Aug 2016
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 170 3,337 0 30 Sep 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 533 9,233 0 06 Jun 2015
Weight Uncertainty in Neural Networks Charles Blundell Julien Cornebise Koray Kavukcuoglu Daan Wierstra UQCV BDL 130 1,878 0 20 May 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.1K 149,474 0 22 Dec 2014