MolGAN: An implicit generative model for small molecular graphs

30 May 2018

Papers citing "MolGAN: An implicit generative model for small molecular graphs"

40 / 140 papers shown

Title
A Deep Generative Model for Molecule Optimization via One Fragment Modification Ziqi Chen Martin Renqiang Min S. Parthasarathy Xia Ning 21 61 0 08 Dec 2020
Symmetry-Aware Actor-Critic for 3D Molecular Design G. Simm Robert Pinsler Gábor Csányi José Miguel Hernández-Lobato AI4CE 26 64 0 25 Nov 2020
Computing Graph Neural Networks: A Survey from Algorithms to Accelerators S. Abadal Akshay Jain Robert Guirado Jorge López-Alonso Eduard Alarcón GNN 27 225 0 30 Sep 2020
Scaffold-constrained molecular generation Maxime Langevin H. Minoux M. Levesque M. Bianciotto 15 45 0 15 Sep 2020
A Systematic Survey on Deep Generative Models for Graph Generation Xiaojie Guo Liang Zhao MedIm 44 147 0 13 Jul 2020
MoFlow: An Invertible Flow Model for Generating Molecular Graphs Chengxi Zang Fei-Yue Wang BDL 14 280 0 17 Jun 2020
Deep Learning and Knowledge-Based Methods for Computer Aided Molecular Design -- Toward a Unified Approach: State-of-the-Art and Future Directions Abdulelah S. Alshehri R. Gani Fengqi You AI4CE 30 83 0 18 May 2020
Autonomous discovery in the chemical sciences part II: Outlook Connor W. Coley Natalie S. Eyke K. Jensen 23 171 0 30 Mar 2020
A Survey of Deep Learning for Scientific Discovery M. Raghu Erica Schmidt OOD AI4CE 38 120 0 26 Mar 2020
A comprehensive study on the prediction reliability of graph neural networks for virtual screening Soojung Yang K. Lee Seongok Ryu 19 7 0 17 Mar 2020
Deterministic Decoding for Discrete Data in Variational Autoencoders Daniil Polykovskiy Dmitry Vetrov OffRL 21 8 0 04 Mar 2020
Reinforcement Learning for Molecular Design Guided by Quantum Mechanics G. Simm Robert Pinsler José Miguel Hernández-Lobato AI4CE 8 82 0 18 Feb 2020
Graph Deconvolutional Generation Daniel Flam-Shepherd Tony C Wu Alán Aspuru-Guzik BDL 25 31 0 14 Feb 2020
Hierarchical Generation of Molecular Graphs using Structural Motifs Wengong Jin Regina Barzilay Tommi Jaakkola 21 279 0 08 Feb 2020
GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation Chence Shi Minkai Xu Zhaocheng Zhu Weinan Zhang Ming Zhang Jian Tang 43 425 0 26 Jan 2020
GraphGen: A Scalable Approach to Domain-agnostic Labeled Graph Generation Nikhil Goyal Harsh Jain Sayan Ranu 10 90 0 22 Jan 2020
A Gentle Introduction to Deep Learning for Graphs D. Bacciu Federico Errica A. Micheli Marco Podda AI4CE GNN 42 276 0 29 Dec 2019
Molecular Generative Model Based On Adversarially Regularized Autoencoder S. Hong Jaechang Lim Seongok Ryu W. Kim GAN DRL GNN 26 63 0 13 Nov 2019
G2SAT: Learning to Generate SAT Formulas Jiaxuan You Haoze Wu Clark W. Barrett R. Ramanujan J. Leskovec NAI 19 35 0 29 Oct 2019
Study of Deep Generative Models for Inorganic Chemical Compositions Yoshihide Sawada Koji Morikawa Mikiya Fujii GAN 12 13 0 25 Oct 2019
NEAR: Neighborhood Edge AggregatoR for Graph Classification Cheolhyeong Kim Haeseong Moon H. Hwang GNN 17 5 0 06 Sep 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 27 92 0 20 Aug 2019
Graph Neural Based End-to-end Data Association Framework for Online Multiple-Object Tracking Xiaolong Jiang Peizhao Li Yanjing Li Xiantong Zhen VOT 26 32 0 11 Jul 2019
Deep Set Prediction Networks Yan Zhang Jonathon S. Hare Adam Prugel-Bennett 17 107 0 15 Jun 2019
Neural Consciousness Flow Xiaoran Xu Wei Feng Zhiqing Sun Zhihong Deng GNN AI4CE 25 2 0 30 May 2019
Drug-Drug Adverse Effect Prediction with Graph Co-Attention Andreea Deac Yu-Hsiang Huang Petar Velickovic Pietro Lió Jian Tang 20 77 0 02 May 2019
D-VAE: A Variational Autoencoder for Directed Acyclic Graphs Muhan Zhang Shali Jiang Zhicheng Cui Roman Garnett Yixin Chen GNN BDL CML 24 196 0 24 Apr 2019
Adversarial Out-domain Examples for Generative Models Dario Pasquini Marco Mingione M. Bernaschi WIGM SILM AAML 15 6 0 07 Mar 2019
Learning to Sample Hard Instances for Graph Algorithms Ryoma Sato M. Yamada H. Kashima 16 1 0 26 Feb 2019
A Comprehensive Survey on Graph Neural Networks Zonghan Wu Shirui Pan Fengwen Chen Guodong Long Chengqi Zhang Philip S. Yu FaML GNN AI4TS AI4CE 159 8,356 0 03 Jan 2019
Graph Neural Networks: A Review of Methods and Applications Jie Zhou Ganqu Cui Shengding Hu Zhengyan Zhang Cheng Yang Zhiyuan Liu Lifeng Wang Changcheng Li Maosong Sun AI4CE GNN 28 5,396 0 20 Dec 2018
Deep Learning on Graphs: A Survey Ziwei Zhang Peng Cui Wenwu Zhu GNN 39 1,320 0 11 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
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
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
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 94 3,078 0 04 Jun 2018
Conditional molecular design with deep generative models Seokho Kang Kyunghyun Cho BDL 157 183 0 30 Apr 2018
Junction Tree Variational Autoencoder for Molecular Graph Generation Wengong Jin Regina Barzilay Tommi Jaakkola 224 1,338 0 12 Feb 2018
Constrained Bayesian Optimization for Automatic Chemical Design Ryan-Rhys Griffiths José Miguel Hernández-Lobato BDL 39 76 0 16 Sep 2017
Geometric deep learning: going beyond Euclidean data M. Bronstein Joan Bruna Yann LeCun Arthur Szlam P. Vandergheynst GNN 253 3,239 0 24 Nov 2016