Application of generative autoencoder in de novo molecular design

21 November 2017

Papers citing "Application of generative autoencoder in de novo molecular design"

22 / 22 papers shown

Title
A Comprehensive Benchmarking Platform for Deep Generative Models in Molecular Design Adarsh Singh ELM 20 0 0 19 May 2025
Learning to generate feasible graphs using graph grammars Stefan Mautner Rolf Backofen Fabrizio Costa 43 0 0 10 Jan 2025
Overcoming Order in Autoregressive Graph Generation Edo Cohen-Karlik Eyal Rozenberg Daniel Freedman 36 1 0 04 Feb 2024
Improving Molecule Properties Through 2-Stage VAE Chenghui Zhou Barnabás Póczós DRL 28 1 0 06 Dec 2022
Computer-Aided Multi-Objective Optimization in Small Molecule Discovery Jenna C. Fromer Connor W. Coley 32 66 0 13 Oct 2022
Fast-Image2Point: Towards Real-Time Point Cloud Reconstruction of a Single Image using 3D Supervision AmirHossein Zamani A. Aghdam K. Ghaffari 3DV 3DPC 27 1 0 20 Sep 2022
Artificial Intelligence in Drug Discovery: Applications and Techniques Jianyuan Deng Zhibo Yang Iwao Ojima Dimitris Samaras Fusheng Wang AI4TS 35 100 0 09 Jun 2021
Dataset Bias in the Natural Sciences: A Case Study in Chemical Reaction Prediction and Synthesis Design Ryan-Rhys Griffiths P. Schwaller Alpha A. Lee AI4CE 43 19 0 06 May 2021
Polygrammar: Grammar for Digital Polymer Representation and Generation Minghao Guo Wan Shou L. Makatura Timothy Erps Michael Foshey Wojciech Matusik 35 24 0 05 May 2021
Graph Polish: A Novel Graph Generation Paradigm for Molecular Optimization Chaojie Ji Yijia Zheng Ruxin Wang Yunpeng Cai Hongyan Wu 26 18 0 14 Aug 2020
Reinforcement Learning for Molecular Design Guided by Quantum Mechanics G. Simm Robert Pinsler José Miguel Hernández-Lobato AI4CE 21 82 0 18 Feb 2020
Symmetry-adapted generation of 3d point sets for the targeted discovery of molecules Niklas W. A. Gebauer M. Gastegger Kristof T. Schütt 40 201 0 02 Jun 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 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
Molecular Transformer - A Model for Uncertainty-Calibrated Chemical Reaction Prediction P. Schwaller Teodoro Laino John McGuinness A. Horváth Constantine Bekas A. Lee 30 719 0 06 Nov 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
Powerful, transferable representations for molecules through intelligent task selection in deep multitask networks Clyde Fare Lukas Turcani Edward O. Pyzer-Knapp 32 13 0 17 Sep 2018
Latent Molecular Optimization for Targeted Therapeutic Design Tristan Aumentado-Armstrong 15 41 0 05 Sep 2018
Deep Learning in Pharmacogenomics: From Gene Regulation to Patient Stratification Alexandr A Kalinin Gerald A. Higgins Narathip Reamaroon S. M. Reza Soroushmehr Ari Allyn-Feuer I. Dinov Kayvan Najarian B. Athey OOD 36 122 0 25 Jan 2018
Multi-Objective De Novo Drug Design with Conditional Graph Generative Model Yibo Li L. Zhang Zhenming Liu 43 335 0 18 Jan 2018
Constrained Bayesian Optimization for Automatic Chemical Design Ryan-Rhys Griffiths José Miguel Hernández-Lobato BDL 39 76 0 16 Sep 2017
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 64 2,885 0 07 Oct 2016