Molecular De Novo Design through Deep Reinforcement Learning

25 April 2017

Papers citing "Molecular De Novo Design through Deep Reinforcement Learning"

50 / 253 papers shown

Title
Synthetic Data for Deep Learning Sergey I. Nikolenko 46 348 0 25 Sep 2019
Deep Generative Model for Sparse Graphs using Text-Based Learning with Augmentation in Generative Examination Networks R. V. Deursen Guillaume Godin 17 1 0 24 Sep 2019
GEN: Highly Efficient SMILES Explorer Using Autodidactic Generative Examination Networks R. V. Deursen P. Ertl Igor V. Tetko Guillaume Godin 6 32 0 10 Sep 2019
Reinforcement Learning in Healthcare: A Survey Chao Yu Jiming Liu S. Nemati LM&MA OffRL 17 547 0 22 Aug 2019
DeepScaffold: a comprehensive tool for scaffold-based de novo drug discovery using deep learning Yibo Li Jianxing Hu Yanxing Wang Jielong Zhou L. Zhang Zhenming Liu 30 92 0 20 Aug 2019
Generative Models for Automatic Chemical Design Daniel Schwalbe-Koda Rafael Gómez-Bombarelli MedIm AI4CE 32 81 0 02 Jul 2019
Hierarchical Graph-to-Graph Translation for Molecules Wengong Jin Regina Barzilay Tommi Jaakkola 26 16 0 11 Jun 2019
Likelihood Ratios for Out-of-Distribution Detection Jie Jessie Ren Peter J. Liu Emily Fertig Jasper Snoek Ryan Poplin M. DePristo Joshua V. Dillon Balaji Lakshminarayanan OODD 18 716 0 07 Jun 2019
Probabilistic hypergraph grammars for efficient molecular optimization E. Kraev Mark Harley 11 1 0 05 Jun 2019
Scaffold-based molecular design using graph generative model Jaechang Lim Sang-Yeon Hwang Seungsu Kim Seokhyun Moon Woo Youn Kim 25 17 0 31 May 2019
Sequence Modeling of Temporal Credit Assignment for Episodic Reinforcement Learning Yang Liu Yunan Luo Yuanyi Zhong Xi Chen Qiang Liu Jian-wei Peng 9 35 0 31 May 2019
MolecularRNN: Generating realistic molecular graphs with optimized properties Mariya Popova Mykhailo Shvets Junier Oliva Olexandr Isayev GNN 35 164 0 31 May 2019
All SMILES Variational Autoencoder Zaccary Alperstein Artem Cherkasov J. Rolfe DRL 14 38 0 30 May 2019
Leveraging binding-site structure for drug discovery with point-cloud methods Vincent Mallet Carlos G. Oliver N. Moitessier J. Waldispühl 16 7 0 28 May 2019
Towards Interpretable Sparse Graph Representation Learning with Laplacian Pooling Emmanuel Noutahi Dominique Beaini Julien Horwood Sébastien Giguère Prudencio Tossou AI4CE 22 34 0 28 May 2019
Adversarial Learned Molecular Graph Inference and Generation Sebastian Polsterl Christian Wachinger GAN 20 7 0 24 May 2019
Generating protein sequences from antibiotic resistance genes data using Generative Adversarial Networks Prabal Chhibbar Arpita Joshi GAN 8 12 0 28 Apr 2019
Deep learning for molecular design - a review of the state of the art Daniel C. Elton Zois Boukouvalas M. Fuge Peter W. Chung AI4CE 3DV 21 326 0 11 Mar 2019
Interpretable Deep Learning in Drug Discovery Kristina Preuer G. Klambauer F. Rippmann Sepp Hochreiter Thomas Unterthiner 11 88 0 07 Mar 2019
Atomistic structure learning M. Jørgensen H. L. Mortensen S. A. Meldgaard E. L. Kolsbjerg Thomas L. Jacobsen K. H. Sørensen B. Hammer AI4CE 8 36 0 27 Feb 2019
Mol-CycleGAN - a generative model for molecular optimization Łukasz Maziarka Agnieszka Pocha Jan Kaczmarczyk Krzysztof Rataj M. Warchoł 15 241 0 06 Feb 2019
Deep Learning on Attributed Graphs: A Journey from Graphs to Their Embeddings and Back M. Simonovsky BDL GNN 23 1 0 24 Jan 2019
Learning to Design RNA Frederic Runge Daniel Stoll Stefan Falkner Frank Hutter 14 66 0 31 Dec 2018
Learning Multimodal Graph-to-Graph Translation for Molecular Optimization Wengong Jin Kevin Kaichuang Yang Regina Barzilay Tommi Jaakkola 33 224 0 03 Dec 2018
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models Daniil Polykovskiy Alexander Zhebrak Benjamín Sánchez-Lengeling Sergey Golovanov Oktai Tatanov ... Simon Johansson Hongming Chen Sergey I. Nikolenko Alán Aspuru-Guzik Alex Zhavoronkov ELM 194 633 0 29 Nov 2018
DEFactor: Differentiable Edge Factorization-based Probabilistic Graph Generation Rim Assouel Mohamed Ahmed Marwin H. S. Segler Amir Saffari Yoshua Bengio 19 54 0 24 Nov 2018
GuacaMol: Benchmarking Models for De Novo Molecular Design Nathan Brown Marco Fiscato Marwin H. S. Segler Alain C. Vaucher ELM 44 691 0 22 Nov 2018
KekuleScope: prediction of cancer cell line sensitivity and compound potency using convolutional neural networks trained on compound images I. Cortés-Ciriano A. Bender MedIm 27 51 0 22 Nov 2018
Optimization of Molecules via Deep Reinforcement Learning Zhenpeng Zhou S. Kearnes Li Li R. Zare Patrick F. Riley AI4CE 16 532 0 19 Oct 2018
Encoding Robust Representation for Graph Generation Dongmian Zou Gilad Lerman GNN 22 0 0 28 Sep 2018
Deep Confidence: A Computationally Efficient Framework for Calculating Reliable Errors for Deep Neural Networks I. Cortés-Ciriano A. Bender OOD UQCV 25 60 0 24 Sep 2018
Latent Molecular Optimization for Targeted Therapeutic Design Tristan Aumentado-Armstrong 15 41 0 05 Sep 2018
Molecular generative model based on conditional variational autoencoder for de novo molecular design Jaechang Lim Seongok Ryu Jin Woo Kim W. Kim BDL DRL 25 325 0 15 Jun 2018
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation Jiaxuan You Bowen Liu Rex Ying Vijay S. Pande J. Leskovec GNN 203 885 0 07 Jun 2018
Constrained Graph Variational Autoencoders for Molecule Design Qi Liu Miltiadis Allamanis Marc Brockschmidt Alexander L. Gaunt BDL 6 449 0 23 May 2018
Conditional molecular design with deep generative models Seokho Kang Kyunghyun Cho BDL 159 183 0 30 Apr 2018
Accelerating Prototype-Based Drug Discovery using Conditional Diversity Networks Shahar Harel Kira Radinsky 9 21 0 08 Apr 2018
Feedback GAN (FBGAN) for DNA: a Novel Feedback-Loop Architecture for Optimizing Protein Functions Anvita Gupta James Zou AI4CE 8 55 0 05 Apr 2018
Graphite: Iterative Generative Modeling of Graphs Aditya Grover Aaron Zweig Stefano Ermon BDL 16 296 0 28 Mar 2018
Fréchet ChemNet Distance: A metric for generative models for molecules in drug discovery Kristina Preuer Philipp Renz Thomas Unterthiner Sepp Hochreiter G. Klambauer MedIm 18 324 0 26 Mar 2018
Learning Deep Generative Models of Graphs Yujia Li Oriol Vinyals Chris Dyer Razvan Pascanu Peter W. Battaglia GNN AI4CE 29 654 0 08 Mar 2018
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models Jiaxuan You Rex Ying Xiang Ren William L. Hamilton J. Leskovec GNN BDL 41 831 0 24 Feb 2018
NeVAE: A Deep Generative Model for Molecular Graphs Bidisha Samanta A. De G. Jana P. Chattaraj Niloy Ganguly Manuel Gomez Rodriguez GNN DRL BDL DiffM 22 211 0 14 Feb 2018
GraphVAE: Towards Generation of Small Graphs Using Variational Autoencoders M. Simonovsky N. Komodakis GNN BDL 24 833 0 09 Feb 2018
Multi-Objective De Novo Drug Design with Conditional Graph Generative Model Yibo Li L. Zhang Zhenming Liu 35 335 0 18 Jan 2018
In silico generation of novel, drug-like chemical matter using the LSTM neural network P. Ertl Richard A. Lewis E. Martin V. Polyakov 17 59 0 20 Dec 2017
Development and evaluation of a deep learning model for protein-ligand binding affinity prediction Marta M. Stepniewska-Dziubinska P. Zielenkiewicz P. Siedlecki 21 437 0 19 Dec 2017
Generating and designing DNA with deep generative models N. Killoran Leo J. Lee Andrew Delong David Duvenaud B. Frey AI4CE 24 145 0 17 Dec 2017
Deep Reinforcement Learning for De-Novo Drug Design Mariya Popova Olexandr Isayev Alexander Tropsha 16 1,002 0 29 Nov 2017
Application of generative autoencoder in de novo molecular design T. Blaschke Marcus Olivecrona O. Engkvist J. Bajorath Hongming Chen AI4CE 36 343 0 21 Nov 2017