Molecular generative model based on conditional variational autoencoder for de novo molecular design

15 June 2018

Papers citing "Molecular generative model based on conditional variational autoencoder for de novo molecular design"

33 / 33 papers shown

Title
MetaMolGen: A Neural Graph Motif Generation Model for De Novo Molecular Design Zimo Yan Jie Zhang Zheng Xie Chang-rui Liu Yong-Jin Liu Yiping Song 36 0 0 22 Apr 2025
Bayesian Flow Is All You Need to Sample Out-of-Distribution Chemical Spaces Nianze Tao OOD OODD BDL 108 0 0 16 Dec 2024
Uncertainty-enabled machine learning for emulation of regional sea-level change caused by the Antarctic Ice Sheet Myungsoo Yoo Giri Gopalan Matthew J. Hoffman Sophie Coulson Holly Kyeore Han C. Wikle Trevor Hillebrand AI4Cl 18 2 0 21 Jun 2024
Overcoming Order in Autoregressive Graph Generation Edo Cohen-Karlik Eyal Rozenberg Daniel Freedman 34 1 0 04 Feb 2024
Learning from small data sets: Patch-based regularizers in inverse problems for image reconstruction Moritz Piening Fabian Altekrüger J. Hertrich Paul Hagemann Andrea Walther Gabriele Steidl 24 6 0 27 Dec 2023
Language models in molecular discovery Chaoqi Wang Yibo Jiang Chenghao Yang Han Liu Yuxin Chen 23 7 0 28 Sep 2023
Diffusion probabilistic models enhance variational autoencoder for crystal structure generative modeling T. Pakornchote Natthaphon Choomphon-anomakhun Sorrjit Arrerut C. Atthapak S. Khamkaeo Thiparat Chotibut T. Bovornratanaraks DiffM 29 17 0 04 Aug 2023
Coupled Variational Autoencoder Xiaoran Hao Patrick Shafto BDL DRL 24 4 0 05 Jun 2023
GraphGANFed: A Federated Generative Framework for Graph-Structured Molecules Towards Efficient Drug Discovery Daniel Manu Jingjing Yao Wuji Liu Xiang Sun FedML 35 6 0 11 Apr 2023
Conditional Generative Models are Provably Robust: Pointwise Guarantees for Bayesian Inverse Problems Fabian Altekrüger Paul Hagemann Gabriele Steidl TPM 26 9 0 28 Mar 2023
Deep Reinforcement Learning for Inverse Inorganic Materials Design Elton Pan Christopher Karpovich E. Olivetti AI4CE 19 11 0 21 Oct 2022
Computer-Aided Multi-Objective Optimization in Small Molecule Discovery Jenna C. Fromer Connor W. Coley 29 67 0 13 Oct 2022
Modular Flows: Differential Molecular Generation Yogesh Verma Samuel Kaski Markus Heinonen Vikas K. Garg 29 14 0 12 Oct 2022
Exploring Chemical Space with Score-based Out-of-distribution Generation Seul Lee Jaehyeong Jo Sung Ju Hwang OODD 30 75 0 06 Jun 2022
Tyger: Task-Type-Generic Active Learning for Molecular Property Prediction Kuangqi Zhou Kaixin Wang Jiashi Feng Jian Tang Tingyang Xu Xinchao Wang 29 1 0 23 May 2022
Conditional $β$ -VAE for De Novo Molecular Generation Ryan J. Richards A. Groener BDL DRL 24 10 0 01 May 2022
MGCVAE: Multi-objective Inverse Design via Molecular Graph Conditional Variational Autoencoder Myeong-Sung Lee K. Min 33 41 0 14 Feb 2022
De Novo Molecular Generation with Stacked Adversarial Model Yuansan Liu James Bailey GAN BDL 16 1 0 24 Oct 2021
Artificial Intelligence in Drug Discovery: Applications and Techniques Jianyuan Deng Zhibo Yang Iwao Ojima Dimitris Samaras Fusheng Wang AI4TS 23 100 0 09 Jun 2021
Polygrammar: Grammar for Digital Polymer Representation and Generation Minghao Guo Wan Shou L. Makatura Timothy Erps Michael Foshey Wojciech Matusik 32 24 0 05 May 2021
Advances in Electron Microscopy with Deep Learning Jeffrey M. Ede 32 2 0 04 Jan 2021
Generating 3D Molecular Structures Conditional on a Receptor Binding Site with Deep Generative Models Tomohide Masuda Matthew Ragoza D. Koes DiffM 34 52 0 16 Oct 2020
Review: Deep Learning in Electron Microscopy Jeffrey M. Ede 34 79 0 17 Sep 2020
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 30 83 0 18 May 2020
Reinforcement Learning for Molecular Design Guided by Quantum Mechanics G. Simm Robert Pinsler José Miguel Hernández-Lobato AI4CE 18 82 0 18 Feb 2020
Molecular Generative Model Based On Adversarially Regularized Autoencoder S. Hong Jaechang Lim Seongok Ryu W. Kim GAN DRL GNN 28 63 0 13 Nov 2019
Study of Deep Generative Models for Inorganic Chemical Compositions Yoshihide Sawada Koji Morikawa Mikiya Fujii GAN 17 13 0 25 Oct 2019
Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules Niklas W. A. Gebauer M. Gastegger Kristof T. Schütt 26 201 0 02 Jun 2019
GuacaMol: Benchmarking Models for De Novo Molecular Design Nathan Brown Marco Fiscato Marwin H. S. Segler Alain C. Vaucher ELM 44 691 0 22 Nov 2018
Optimization of Molecules via Deep Reinforcement Learning Zhenpeng Zhou S. Kearnes Li Li R. Zare Patrick F. Riley AI4CE 16 532 0 19 Oct 2018
Powerful, transferable representations for molecules through intelligent task selection in deep multitask networks Clyde Fare Lukas Turcani Edward O. Pyzer-Knapp 24 13 0 17 Sep 2018
Junction Tree Variational Autoencoder for Molecular Graph Generation Wengong Jin Regina Barzilay Tommi Jaakkola 224 1,340 0 12 Feb 2018
Constrained Bayesian Optimization for Automatic Chemical Design Ryan-Rhys Griffiths José Miguel Hernández-Lobato BDL 39 76 0 16 Sep 2017