Improving Chemical Autoencoder Latent Space and Molecular De novo Generation Diversity with Heteroencoders

25 June 2018

Papers citing "Improving Chemical Autoencoder Latent Space and Molecular De novo Generation Diversity with Heteroencoders"

9 / 9 papers shown

Title
MolX: Enhancing Large Language Models for Molecular Learning with A Multi-Modal Extension Khiem Le Zhichun Guo Kaiwen Dong Xiaobao Huang B. Nan Roshni G. Iyer Xiangliang Zhang Olaf Wiest Wei Wang Nitesh V. Chawla 34 8 0 10 Jun 2024
Faster and more diverse de novo molecular optimization with double-loop reinforcement learning using augmented SMILES E. Bjerrum Christian Margreitter Thomas Blaschke Raquel Lopez-Rios de Castro 32 11 0 22 Oct 2022
An Unpooling Layer for Graph Generation Yi Guo Dongmian Zou Gilad Lerman 10 2 0 04 Jun 2022
MGCVAE: Multi-objective Inverse Design via Molecular Graph Conditional Variational Autoencoder Myeong-Sung Lee K. Min 33 41 0 14 Feb 2022
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 22 83 0 18 May 2020
Autonomous discovery in the chemical sciences part II: Outlook Connor W. Coley Natalie S. Eyke K. Jensen 21 171 0 30 Mar 2020
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
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 179 633 0 29 Nov 2018
Constrained Bayesian Optimization for Automatic Chemical Design Ryan-Rhys Griffiths José Miguel Hernández-Lobato BDL 37 76 0 16 Sep 2017