Junction Tree Variational Autoencoder for Molecular Graph Generation

12 February 2018

Papers citing "Junction Tree Variational Autoencoder for Molecular Graph Generation"

50 / 248 papers shown

Title
GOOD: A Graph Out-of-Distribution Benchmark Shurui Gui Xiner Li Limei Wang Shuiwang Ji OOD 33 116 0 16 Jun 2022
Long Range Graph Benchmark Vijay Prakash Dwivedi Ladislav Rampášek Mikhail Galkin Alipanah Parviz Guy Wolf A. Luu Dominique Beaini 26 195 0 16 Jun 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
An Unpooling Layer for Graph Generation Yi Guo Dongmian Zou Gilad Lerman 16 2 0 04 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
3DLinker: An E(3) Equivariant Variational Autoencoder for Molecular Linker Design Yinan Huang Xing Peng Jianzhu Ma Muhan Zhang BDL 30 48 0 15 May 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
SPECTRE: Spectral Conditioning Helps to Overcome the Expressivity Limits of One-shot Graph Generators Karolis Martinkus Andreas Loukas Nathanael Perraudin Roger Wattenhofer 42 67 0 04 Apr 2022
SELFIES and the future of molecular string representations Mario Krenn Qianxiang Ai Senja Barthel Nessa Carson Angelo Frei ... Andrew Wang Andrew D. White Adamo Young Rose Yu A. Aspuru‐Guzik 38 149 0 31 Mar 2022
Automatic Identification of Chemical Moieties Jonas Lederer M. Gastegger Kristof T. Schütt Michael C. Kampffmeyer Klaus-Robert Muller Oliver T. Unke 21 5 0 30 Mar 2022
MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design Yuanqi Du Tianfan Fu Jimeng Sun Shengchao Liu AI4CE 33 86 0 28 Mar 2022
Accelerating Bayesian Optimization for Biological Sequence Design with Denoising Autoencoders Samuel Stanton Wesley J. Maddox Nate Gruver Phillip M. Maffettone E. Delaney Peyton Greenside A. Wilson BDL 38 89 0 23 Mar 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
GeoDiff: a Geometric Diffusion Model for Molecular Conformation Generation Minkai Xu Lantao Yu Yang Song Chence Shi Stefano Ermon Jian Tang BDL DiffM 52 496 0 06 Mar 2022
Variational Autoencoders Without the Variation Gregory A. Daly J. Fieldsend G. Tabor 31 2 0 01 Mar 2022
Multi-Objective Latent Space Optimization of Generative Molecular Design Models Naﬁz Abeer Nathan M. Urban Ryan Weil Francis J. Alexander Byung-Jun Yoon 23 15 0 01 Mar 2022
Bayesian Sequential Stacking Algorithm for Concurrently Designing Molecules and Synthetic Reaction Networks Qi Zhang Chang Liu Stephen Wu Ryo Yoshida BDL 32 3 0 01 Mar 2022
Interpretable Molecular Graph Generation via Monotonic Constraints Yuanqi Du Xiaojie Guo Amarda Shehu Liang Zhao 65 19 0 28 Feb 2022
Learning to Discover Medicines T. Nguyen Thin Nguyen T. Tran 34 1 0 14 Feb 2022
MGCVAE: Multi-objective Inverse Design via Molecular Graph Conditional Variational Autoencoder Myeong-Sung Lee K. Min 33 41 0 14 Feb 2022
Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equations Jaehyeong Jo Seul Lee Sung Ju Hwang DiffM 22 211 0 05 Feb 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 58 69 0 28 Jan 2022
Improving Subgraph Recognition with Variational Graph Information Bottleneck Junchi Yu Jie Cao Ran He 22 53 0 18 Dec 2021
Genetic Algorithm for Constrained Molecular Inverse Design Yurim Lee Gydam Choi Minsug Yoon Cheongwon Kim 29 1 0 07 Dec 2021
Deep Molecular Representation Learning via Fusing Physical and Chemical Information Shuwen Yang Ziyao Li Guojie Song Lingsheng Cai AI4CE 40 28 0 28 Nov 2021
Directional Message Passing on Molecular Graphs via Synthetic Coordinates Johannes Klicpera Chandan Yeshwanth Stephan Günnemann 42 35 0 08 Nov 2021
Brick-by-Brick: Combinatorial Construction with Deep Reinforcement Learning H. Chung Jungtaek Kim Boris Knyazev Jinhwi Lee Graham W. Taylor Jaesik Park Minsu Cho SSL OffRL 18 20 0 29 Oct 2021
Permutation invariant graph-to-sequence model for template-free retrosynthesis and reaction prediction Zhengkai Tu Connor W. Coley 30 90 0 19 Oct 2021
Equivariant Subgraph Aggregation Networks Beatrice Bevilacqua Fabrizio Frasca Derek Lim Balasubramaniam Srinivasan Chen Cai G. Balamurugan M. Bronstein Haggai Maron 56 176 0 06 Oct 2021
Hit and Lead Discovery with Explorative RL and Fragment-based Molecule Generation Soojung Yang Doyeong Hwang Seul Lee Seongok Ryu Sung Ju Hwang 34 67 0 04 Oct 2021
Motif-based Graph Self-Supervised Learning for Molecular Property Prediction Zaixin Zhang Qi Liu Hao Wang Chengqiang Lu Chee-Kong Lee SSL AI4CE 37 250 0 03 Oct 2021
Simulated annealing for optimization of graphs and sequences Xianggen Liu Pengyong Li Fandong Meng Hao Zhou Huasong Zhong Jie Zhou Lili Mou Sen Song 49 19 0 01 Oct 2021
Vitruvion: A Generative Model of Parametric CAD Sketches Ari Seff Wenda Zhou Nick Richardson Ryan P. Adams 27 64 0 29 Sep 2021
Differentiable Scaffolding Tree for Molecular Optimization Tianfan Fu Wenhao Gao Cao Xiao Jacob Yasonik Connor W. Coley Jimeng Sun 25 76 0 22 Sep 2021
PluGeN: Multi-Label Conditional Generation From Pre-Trained Models Maciej Wołczyk Magdalena Proszewska Lukasz Maziarka Maciej Ziȩba Patryk Wielopolski Rafał Kurczab Marek Śmieja DRL 27 5 0 18 Sep 2021
Self-learn to Explain Siamese Networks Robustly Chao Chen Yifan Shen Guixiang Ma Xiangnan Kong S. Rangarajan Xi Zhang Sihong Xie 46 5 0 15 Sep 2021
Machine learning modeling of family wide enzyme-substrate specificity screens Samuel Goldman Ria Das Kevin Kaichuang Yang Connor W. Coley 27 54 0 08 Sep 2021
Multiscale Spatio-Temporal Graph Neural Networks for 3D Skeleton-Based Motion Prediction Maosen Li Siheng Chen Yangheng Zhao Ya Zhang Yanfeng Wang Qi Tian 3DH 23 74 0 25 Aug 2021
Unconditional Scene Graph Generation Sarthak Garg Helisa Dhamo Azade Farshad Sabrina Musatian Nassir Navab F. Tombari 18 23 0 12 Aug 2021
Geometric Deep Learning on Molecular Representations Kenneth Atz F. Grisoni G. Schneider AI4CE 34 287 0 26 Jul 2021
Rapid Neural Architecture Search by Learning to Generate Graphs from Datasets Hayeon Lee Eunyoung Hyung Sung Ju Hwang 40 43 0 02 Jul 2021
Quantitative Evaluation of Explainable Graph Neural Networks for Molecular Property Prediction Jiahua Rao Shuangjia Zheng Yuedong Yang 21 46 0 01 Jul 2021
Improving black-box optimization in VAE latent space using decoder uncertainty Pascal Notin José Miguel Hernández-Lobato Y. Gal 32 61 0 30 Jun 2021
Molecule Generation by Principal Subgraph Mining and Assembling Xiangzhe Kong Wenbing Huang Zhixing Tan Yang Liu GNN 21 45 0 29 Jun 2021
DGL-LifeSci: An Open-Source Toolkit for Deep Learning on Graphs in Life Science Mufei Li Jinjing Zhou Jiajing Hu Wenxuan Fan Yangkang Zhang Yaxin Gu George Karypis GNN AI4CE 33 159 0 27 Jun 2021
Geometric learning of the conformational dynamics of molecules using dynamic graph neural networks Michael Ashby Jenna A. Bilbrey 25 4 0 24 Jun 2021
Graph Context Encoder: Graph Feature Inpainting for Graph Generation and Self-supervised Pretraining Oriel Frigo Rémy Brossard David Dehaene 37 1 0 18 Jun 2021
Planning Spatial Networks with Monte Carlo Tree Search Victor-Alexandru Darvariu Stephen Hailes Mirco Musolesi 27 7 0 12 Jun 2021