Molecular Generative Model Based On Adversarially Regularized Autoencoder

13 November 2019

Papers citing "Molecular Generative Model Based On Adversarially Regularized Autoencoder"

6 / 6 papers shown

Title
Decoding Structure-Spectrum Relationships with Physically Organized Latent Spaces Zhu Liang Matthew R. Carbone Wei Chen Fanchen Meng Eli Stavitski D. Lu M. Hybertsen Xiaohui Qu 11 7 0 11 Jan 2023
LatentGAN Autoencoder: Learning Disentangled Latent Distribution Sanket Kalwar Animikh Aich Tanay Dixit Adit Chhabra DRL 29 0 0 05 Apr 2022
Data-Driven Discovery of Molecular Photoswitches with Multioutput Gaussian Processes Ryan-Rhys Griffiths Jake L. Greenfield Aditya R. Thawani Arian R. Jamasb Henry B. Moss Anthony Bourached Penelope Jones William McCorkindale Alexander A. Aldrick Matthew J. Fuchter Alpha A. Lee 30 13 0 28 Jun 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
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 164 183 0 30 Apr 2018