Learning Latent Space Energy-Based Prior Model for Molecule Generation

19 October 2020

Papers citing "Learning Latent Space Energy-Based Prior Model for Molecule Generation"

7 / 7 papers shown

Title
A Deep Generative Model for Fragment-Based Molecule Generation Marco Podda D. Bacciu Alessio Micheli VLM BDL 55 52 0 28 Feb 2020
GraphAF: a Flow-based Autoregressive Model for Molecular Graph Generation Chence Shi Minkai Xu Zhaocheng Zhu Weinan Zhang Ming Zhang Jian Tang 168 437 0 26 Jan 2020
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation Jiaxuan You Bowen Liu Rex Ying Vijay S. Pande J. Leskovec GNN 287 902 0 07 Jun 2018
Constrained Graph Variational Autoencoders for Molecule Design Qi Liu Miltiadis Allamanis Marc Brockschmidt Alexander L. Gaunt BDL 75 456 0 23 May 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 60 218 0 14 Feb 2018
GraphVAE: Towards Generation of Small Graphs Using Variational Autoencoders M. Simonovsky N. Komodakis GNN BDL 114 850 0 09 Feb 2018
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 161 2,929 0 07 Oct 2016