Junction Tree Variational Autoencoder for Molecular Graph Generation

12 February 2018

Papers citing "Junction Tree Variational Autoencoder for Molecular Graph Generation"

50 / 250 papers shown

Title
Deterministic Decoding for Discrete Data in Variational Autoencoders Daniil Polykovskiy Dmitry Vetrov OffRL 21 8 0 04 Mar 2020
Generalization and Representational Limits of Graph Neural Networks Vikas K. Garg Stefanie Jegelka Tommi Jaakkola GNN 26 304 0 14 Feb 2020
Can Graph Neural Networks Count Substructures? Zhengdao Chen Lei Chen Soledad Villar Joan Bruna GNN 57 319 0 10 Feb 2020
Hierarchical Generation of Molecular Graphs using Structural Motifs Wengong Jin Regina Barzilay Tommi Jaakkola 21 279 0 08 Feb 2020
A deep-learning view of chemical space designed to facilitate drug discovery P. Maragakis Hunter M. Nisonoff B. Cole D. Shaw 41 28 0 07 Feb 2020
FastGAE: Scalable Graph Autoencoders with Stochastic Subgraph Decoding Guillaume Salha-Galvan Romain Hennequin Jean-Baptiste Remy Manuel Moussallam Michalis Vazirgiannis GNN BDL 29 6 0 05 Feb 2020
TaxoExpan: Self-supervised Taxonomy Expansion with Position-Enhanced Graph Neural Network Jiaming Shen Zhihong Shen Chenyan Xiong Chi Wang Kuansan Wang Jiawei Han 27 74 0 26 Jan 2020
GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation Chence Shi Minkai Xu Zhaocheng Zhu Weinan Zhang Ming Zhang Jian Tang 64 426 0 26 Jan 2020
GraphGen: A Scalable Approach to Domain-agnostic Labeled Graph Generation Nikhil Goyal Harsh Jain Sayan Ranu 18 91 0 22 Jan 2020
Machine learning and AI-based approaches for bioactive ligand discovery and GPCR-ligand recognition S. Raschka Benjamin Kaufman AI4CE 24 67 0 17 Jan 2020
Graph-Bert: Only Attention is Needed for Learning Graph Representations Jiawei Zhang Haopeng Zhang Congying Xia Li Sun 31 298 0 15 Jan 2020
A Gentle Introduction to Deep Learning for Graphs D. Bacciu Federico Errica Alessio Micheli Marco Podda AI4CE GNN 51 277 0 29 Dec 2019
CORE: Automatic Molecule Optimization Using Copy & Refine Strategy Tianfan Fu Cao Xiao Jimeng Sun 31 63 0 23 Nov 2019
G2SAT: Learning to Generate SAT Formulas Jiaxuan You Haoze Wu Clark W. Barrett R. Ramanujan J. Leskovec NAI 27 35 0 29 Oct 2019
Hyperbolic Graph Neural Networks Qi Liu Maximilian Nickel Douwe Kiela AI4CE GNN 45 370 0 28 Oct 2019
Learning to Make Generalizable and Diverse Predictions for Retrosynthesis Benson Chen T. Shen Tommi Jaakkola Regina Barzilay 24 46 0 21 Oct 2019
Augmenting Genetic Algorithms with Deep Neural Networks for Exploring the Chemical Space AkshatKumar Nigam Pascal Friederich Mario Krenn Alán Aspuru-Guzik AI4CE 27 128 0 25 Sep 2019
Synthetic Data for Deep Learning Sergey I. Nikolenko 46 348 0 25 Sep 2019
A Generative Model for Molecular Distance Geometry G. Simm José Miguel Hernández-Lobato GAN 29 107 0 25 Sep 2019
Data-Driven Approach to Encoding and Decoding 3-D Crystal Structures Jordan Hoffmann Louis Maestrati Yoshihide Sawada Jian Tang Jean Michel D. Sellier Yoshua Bengio DiffM 3DV 30 66 0 03 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 30 92 0 20 Aug 2019
GraphBLAST: A High-Performance Linear Algebra-based Graph Framework on the GPU Carl Yang A. Buluç John Douglas Owens GNN 16 97 0 04 Aug 2019
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization Fan-Yun Sun Jordan Hoffmann Vikas Verma Jian Tang SSL 50 840 0 31 Jul 2019
Mixed-Variable Bayesian Optimization Erik A. Daxberger Anastasia Makarova M. Turchetta Andreas Krause 24 51 0 02 Jul 2019
A Two-Step Graph Convolutional Decoder for Molecule Generation Xavier Bresson T. Laurent 25 60 0 08 Jun 2019
Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules Niklas W. A. Gebauer M. Gastegger Kristof T. Schütt 40 201 0 02 Jun 2019
Self-Referencing Embedded Strings (SELFIES): A 100% robust molecular string representation Mario Krenn Florian Hase AkshatKumar Nigam Pascal Friederich Alán Aspuru-Guzik 13 70 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
D-VAE: A Variational Autoencoder for Directed Acyclic Graphs Muhan Zhang Shali Jiang Zhicheng Cui Roman Garnett Yixin Chen GNN BDL CML 32 196 0 24 Apr 2019
Molecular geometry prediction using a deep generative graph neural network Elman Mansimov Omar Mahmood Seokho Kang Kyunghyun Cho 24 183 0 31 Mar 2019
From Variational to Deterministic Autoencoders Partha Ghosh Mehdi S. M. Sajjadi Antonio Vergari Michael J. Black Bernhard Schölkopf DRL 37 269 0 29 Mar 2019
Tiered Latent Representations and Latent Spaces for Molecular Graphs Daniel T. Chang AI4CE BDL 35 7 0 21 Mar 2019
A Degeneracy Framework for Scalable Graph Autoencoders Guillaume Salha-Galvan Romain Hennequin Viet-Anh Tran Michalis Vazirgiannis GNN 29 36 0 23 Feb 2019
Deep Learning on Attributed Graphs: A Journey from Graphs to Their Embeddings and Back M. Simonovsky BDL GNN 29 1 0 24 Jan 2019
LanczosNet: Multi-Scale Deep Graph Convolutional Networks Renjie Liao Zhizhen Zhao R. Urtasun R. Zemel GNN 25 227 0 06 Jan 2019
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 197 633 0 29 Nov 2018
GuacaMol: Benchmarking Models for De Novo Molecular Design Nathan Brown Marco Fiscato Marwin H. S. Segler Alain C. Vaucher ELM 44 692 0 22 Nov 2018
Chemical Structure Elucidation from Mass Spectrometry by Matching Substructures Jing Lim Joshua Wong M. X. Wong Lee Han Eric Tan Hai Leong Chieu Davin Choo Neng Kai Nigel Neo 21 8 0 17 Nov 2018
Molecular Transformer - A Model for Uncertainty-Calibrated Chemical Reaction Prediction P. Schwaller Teodoro Laino John McGuinness A. Horváth Constantine Bekas A. Lee 30 719 0 06 Nov 2018
Optimization of Molecules via Deep Reinforcement Learning Zhenpeng Zhou S. Kearnes Li Li R. Zare Patrick F. Riley AI4CE 27 533 0 19 Oct 2018
Latent Molecular Optimization for Targeted Therapeutic Design Tristan Aumentado-Armstrong 15 41 0 05 Sep 2018
DeepAffinity: Interpretable Deep Learning of Compound-Protein Affinity through Unified Recurrent and Convolutional Neural Networks Mostafa Karimi Di Wu Zhangyang Wang Yang Shen 35 358 0 20 Jun 2018
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation Jiaxuan You Bowen Liu Rex Ying Vijay S. Pande J. Leskovec GNN 206 885 0 07 Jun 2018
MolGAN: An implicit generative model for small molecular graphs Nicola De Cao Thomas Kipf GNN GAN 35 906 0 30 May 2018
Conditional molecular design with deep generative models Seokho Kang Kyunghyun Cho BDL 175 183 0 30 Apr 2018
Attentional Multilabel Learning over Graphs: A Message Passing Approach Kien Do T. Tran Thin Nguyen Svetha Venkatesh 29 17 0 01 Apr 2018
Graphite: Iterative Generative Modeling of Graphs Aditya Grover Aaron Zweig Stefano Ermon BDL 33 296 0 28 Mar 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 on graphs and manifolds using mixture model CNNs Federico Monti Davide Boscaini Jonathan Masci Emanuele Rodolà Jan Svoboda M. Bronstein GNN 260 1,811 0 25 Nov 2016