Molecular Hypergraph Grammar with its Application to Molecular Optimization

8 September 2018

Papers citing "Molecular Hypergraph Grammar with its Application to Molecular Optimization"

24 / 24 papers shown

Title
Molecular Hypergraph Neural Networks Junwu Chen Philippe Schwaller GNN 47 10 0 20 Dec 2023
MHG-GNN: Combination of Molecular Hypergraph Grammar with Graph Neural Network Akihiro Kishimoto Hiroshi Kajino Masataka Hirose Junta Fuchiwaki Indra Priyadarsini Lisa Hamada Hajime Shinohara D. Nakano Seiji Takeda AI4CE 39 4 0 28 Sep 2023
Deep reinforcement learning for process design: Review and perspective Qitong Gao Artur M. Schweidtmann AI4CE 27 14 0 15 Aug 2023
Inverse Protein Folding Using Deep Bayesian Optimization Natalie Maus Yimeng Zeng Daniel A. Anderson Phillip M. Maffettone Aaron C. Solomon Peyton Greenside Osbert Bastani Jacob R. Gardner 28 2 0 25 May 2023
NVDiff: Graph Generation through the Diffusion of Node Vectors Xiaohui Chen Yukun Li Aonan Zhang Liping Liu DiffM 25 21 0 19 Nov 2022
Modular Flows: Differential Molecular Generation Yogesh Verma Samuel Kaski Markus Heinonen Vikas K. Garg 29 14 0 12 Oct 2022
Pocket2Mol: Efficient Molecular Sampling Based on 3D Protein Pockets Xingang Peng Shitong Luo Jiaqi Guan Qi Xie Jian-wei Peng Jianzhu Ma 27 176 0 15 May 2022
Conditional $β$ -VAE for De Novo Molecular Generation Ryan J. Richards A. Groener BDL DRL 24 10 0 01 May 2022
A Survey on Deep Graph Generation: Methods and Applications Yanqiao Zhu Yuanqi Du Yinkai Wang Yichen Xu Jieyu Zhang Qiang Liu Shu Wu 3DV GNN 31 67 0 13 Mar 2022
Bayesian Sequential Stacking Algorithm for Concurrently Designing Molecules and Synthetic Reaction Networks Qi Zhang Chang Liu Stephen Wu Ryo Yoshida BDL 39 3 0 01 Mar 2022
Biases in In Silico Evaluation of Molecular Optimization Methods and Bias-Reduced Evaluation Methodology Hiroshi Kajino Kohei Miyaguchi Takayuki Osogami 59 1 0 28 Jan 2022
Local Latent Space Bayesian Optimization over Structured Inputs Natalie Maus Haydn Thomas Jones Juston Moore Matt J. Kusner John Bradshaw Jacob R. Gardner BDL 61 69 0 28 Jan 2022
Artificial Intelligence in Drug Discovery: Applications and Techniques Jianyuan Deng Zhibo Yang Iwao Ojima Dimitris Samaras Fusheng Wang AI4TS 40 100 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 37 24 0 05 May 2021
GraphDF: A Discrete Flow Model for Molecular Graph Generation Youzhi Luo Keqiang Yan Shuiwang Ji DRL 185 188 0 01 Feb 2021
Barking up the right tree: an approach to search over molecule synthesis DAGs John Bradshaw Brooks Paige Matt J. Kusner Marwin H. S. Segler José Miguel Hernández-Lobato 53 56 0 21 Dec 2020
Utilising Graph Machine Learning within Drug Discovery and Development Thomas Gaudelet Ben Day Arian R. Jamasb Jyothish Soman Cristian Regep ... Jian Tang D. Roblin Tom L. Blundell M. Bronstein J. Taylor-King AI4CE 29 36 0 09 Dec 2020
BOSS: Bayesian Optimization over String Spaces Henry B. Moss Daniel Beck Javier I. González David S. Leslie Paul Rayson 11 68 0 02 Oct 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
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
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 233 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