Syntax-Directed Variational Autoencoder for Structured Data

24 February 2018

Steven Skiena

Papers citing "Syntax-Directed Variational Autoencoder for Structured Data"

21 / 71 papers shown

Title
Generating Sentences from Disentangled Syntactic and Semantic Spaces Yu Bao Hao Zhou Shujian Huang Lei Li Lili Mou Olga Vechtomova Xinyu Dai Jiajun Chen DRL 21 107 0 06 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 19 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 35 201 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
Prototype Propagation Networks (PPN) for Weakly-supervised Few-shot Learning on Category Graph Lu Liu Dinesh Manocha Guodong Long Jing Jiang Lina Yao Chengqi Zhang 24 71 0 10 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
Deep Learning on Attributed Graphs: A Journey from Graphs to Their Embeddings and Back M. Simonovsky BDL GNN 29 1 0 24 Jan 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 161 8,362 0 03 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
Concept-Oriented Deep Learning: Generative Concept Representations Daniel T. Chang DRL GAN BDL 34 12 0 15 Nov 2018
Generating equilibrium molecules with deep neural networks Niklas W. A. Gebauer M. Gastegger Kristof T. Schütt BDL 19 38 0 26 Oct 2018
Efficiently measuring a quantum device using machine learning D. Lennon H. Moon L. Camenzind Liuqi Yu D. Zumbuhl G. Briggs Michael A. Osborne E. Laird N. Ares 14 67 0 23 Oct 2018
Optimization of Molecules via Deep Reinforcement Learning Zhenpeng Zhou S. Kearnes Li Li R. Zare Patrick F. Riley AI4CE 27 532 0 19 Oct 2018
Latent Molecular Optimization for Targeted Therapeutic Design Tristan Aumentado-Armstrong 15 41 0 05 Sep 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
Conditional molecular design with deep generative models Seokho Kang Kyunghyun Cho BDL 175 183 0 30 Apr 2018
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models Jiaxuan You Rex Ying Xiang Ren William L. Hamilton J. Leskovec GNN BDL 43 831 0 24 Feb 2018
Constrained Bayesian Optimization for Automatic Chemical Design Ryan-Rhys Griffiths José Miguel Hernández-Lobato BDL 39 76 0 16 Sep 2017