Optimization of Molecules via Deep Reinforcement Learning

19 October 2018

Papers citing "Optimization of Molecules via Deep Reinforcement Learning"

21 / 71 papers shown

Title
MEG: Generating Molecular Counterfactual Explanations for Deep Graph Networks Danilo Numeroso D. Bacciu 29 38 0 16 Apr 2021
Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development Kexin Huang Tianfan Fu Wenhao Gao Yue Zhao Yusuf Roohani J. Leskovec Connor W. Coley Cao Xiao Jimeng Sun Marinka Zitnik OOD LM&MA 33 263 0 18 Feb 2021
Benchmarking Deep Graph Generative Models for Optimizing New Drug Molecules for COVID-19 Logan T. Ward Jenna A. Bilbrey Sutanay Choudhury Neeraj Kumar Ganesh Sivaraman GNN 27 3 0 09 Feb 2021
A Deep Generative Model for Molecule Optimization via One Fragment Modification Ziqi Chen Martin Renqiang Min Srinivasan Parthasarathy Xia Ning 21 61 0 08 Dec 2020
Symmetry-Aware Actor-Critic for 3D Molecular Design G. Simm Robert Pinsler Gábor Csányi José Miguel Hernández-Lobato AI4CE 29 64 0 25 Nov 2020
Explaining Deep Graph Networks with Molecular Counterfactuals Danilo Numeroso D. Bacciu 13 10 0 09 Nov 2020
Optimizing Molecules using Efficient Queries from Property Evaluations Samuel C. Hoffman Vijil Chenthamarakshan Kahini Wadhawan Pin-Yu Chen Payel Das 39 68 0 03 Nov 2020
Controlled Molecule Generator for Optimizing Multiple Chemical Properties Bonggun Shin Sungsoo Park Jinyeong Bak Joyce C. Ho 22 14 0 26 Oct 2020
Scaffold-constrained molecular generation Maxime Langevin H. Minoux M. Levesque M. Bianciotto 26 46 0 15 Sep 2020
Deep Learning in Protein Structural Modeling and Design Wenhao Gao S. Mahajan Jeremias Sulam Jeffrey J. Gray 29 159 0 16 Jul 2020
A Systematic Survey on Deep Generative Models for Graph Generation Xiaojie Guo Liang Zhao MedIm 44 147 0 13 Jul 2020
Guiding Deep Molecular Optimization with Genetic Exploration Sungsoo Ahn Junsup Kim Hankook Lee Jinwoo Shin 29 70 0 04 Jul 2020
On-the-fly Closed-loop Autonomous Materials Discovery via Bayesian Active Learning A. Kusne Heshan Yu Changming Wu Huairuo Zhang J. Hattrick-Simpers ... Ritesh Agarwal L. Bendersky Mo Li Apurva Mehta Ichiro Takeuchi 9 7 0 11 Jun 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
Hierarchical Generation of Molecular Graphs using Structural Motifs Wengong Jin Regina Barzilay Tommi Jaakkola 21 279 0 08 Feb 2020
Machine learning and AI-based approaches for bioactive ligand discovery and GPCR-ligand recognition S. Raschka Benjamin Kaufman AI4CE 24 67 0 17 Jan 2020
CORE: Automatic Molecule Optimization Using Copy & Refine Strategy Tianfan Fu Cao Xiao Jimeng Sun 31 63 0 23 Nov 2019
Using Attribution to Decode Dataset Bias in Neural Network Models for Chemistry Kevin McCloskey Ankur Taly Federico Monti M. Brenner Lucy J. Colwell 27 85 0 27 Nov 2018
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
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