Strategies for Pre-training Graph Neural Networks

29 May 2019

Papers citing "Strategies for Pre-training Graph Neural Networks"

50 / 300 papers shown

Title
Autobahn: Automorphism-based Graph Neural Nets Erik H. Thiede Wenda Zhou Risi Kondor GNN AI4CE 26 48 0 02 Mar 2021
LogME: Practical Assessment of Pre-trained Models for Transfer Learning Kaichao You Yong Liu Jianmin Wang Mingsheng Long 29 178 0 22 Feb 2021
Self-Supervised Learning of Graph Neural Networks: A Unified Review Yaochen Xie Zhao Xu Jingtun Zhang Zhengyang Wang Shuiwang Ji SSL 41 326 0 22 Feb 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 40 264 0 18 Feb 2021
Few-Shot Graph Learning for Molecular Property Prediction Zhichun Guo Chuxu Zhang Wenhao Yu John E. Herr Olaf Wiest Meng Jiang Nitesh Chawla AI4CE 119 171 0 16 Feb 2021
Large-Scale Representation Learning on Graphs via Bootstrapping S. Thakoor Corentin Tallec M. G. Azar Mehdi Azabou Eva L. Dyer Rémi Munos Petar Velivcković Michal Valko SSL 29 218 0 12 Feb 2021
SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks Bahare Fatemi Layla El Asri Seyed Mehran Kazemi GNN SSL 22 160 0 09 Feb 2021
Interpreting and Unifying Graph Neural Networks with An Optimization Framework Meiqi Zhu Xiao Wang C. Shi Houye Ji Peng Cui AI4CE 54 198 0 28 Jan 2021
Calibrating and Improving Graph Contrastive Learning Kaili Ma Haochen Yang Han Yang Yongqiang Chen James Cheng 49 6 0 27 Jan 2021
Boost then Convolve: Gradient Boosting Meets Graph Neural Networks Sergei Ivanov Liudmila Prokhorenkova AI4CE 53 52 0 21 Jan 2021
GraphAttacker: A General Multi-Task GraphAttack Framework Jinyin Chen Dunjie Zhang Zhaoyan Ming Kejie Huang Wenrong Jiang Chen Cui AAML 38 14 0 18 Jan 2021
Label Contrastive Coding based Graph Neural Network for Graph Classification Yuxiang Ren Jiyang Bai Jiawei Zhang 42 26 0 14 Jan 2021
Graph Neural Networks: Taxonomy, Advances and Trends Yu Zhou Haixia Zheng Xin Huang Shufeng Hao Dengao Li Jumin Zhao AI4TS 27 117 0 16 Dec 2020
Bayesian neural network with pretrained protein embedding enhances prediction accuracy of drug-protein interaction QHwan Kim Joon-Hyuk Ko Sunghoon Kim Nojun Park W. Jhe BDL 34 27 0 15 Dec 2020
Unsupervised Adversarially-Robust Representation Learning on Graphs Jiarong Xu Yang Yang Junru Chen Chunping Wang Xin Jiang Jiangang Lu Yizhou Sun SSL AAML OOD 38 36 0 04 Dec 2020
Advanced Graph and Sequence Neural Networks for Molecular Property Prediction and Drug Discovery Zhengyang Wang Meng Liu Youzhi Luo Zhao Xu Yaochen Xie ... Lei Cai Q. Qi Zhuoning Yuan Tianbao Yang Shuiwang Ji 36 100 0 02 Dec 2020
Molecular representation learning with language models and domain-relevant auxiliary tasks Benedek Fabian T. Edlich H. Gaspar Marwin H. S. Segler Joshua Meyers Marco Fiscato Mohamed Ahmed 13 124 0 26 Nov 2020
Message Passing Networks for Molecules with Tetrahedral Chirality L. Pattanaik O. Ganea Ian Coley K. Jensen W. Green Connor W. Coley GNN 19 23 0 24 Nov 2020
Towards Domain-Agnostic Contrastive Learning Vikas Verma Minh-Thang Luong Kenji Kawaguchi Hieu H. Pham Quoc V. Le SSL 15 116 0 09 Nov 2020
Iterative Graph Self-Distillation Hanlin Zhang Shuai Lin Weiyang Liu Pan Zhou Jian Tang Xiaodan Liang Eric Xing SSL 59 33 0 23 Oct 2020
Self-supervised Graph Learning for Recommendation Jiancan Wu Xiang Wang Fuli Feng Xiangnan He Liang Chen Jianxun Lian Xing Xie SSL 28 1,120 0 21 Oct 2020
Robust Optimization as Data Augmentation for Large-scale Graphs Kezhi Kong Ge Li Mucong Ding Zuxuan Wu Chen Zhu Guohao Li Gavin Taylor Tom Goldstein 106 75 0 19 Oct 2020
ChemBERTa: Large-Scale Self-Supervised Pretraining for Molecular Property Prediction Seyone Chithrananda Gabriel Grand Bharath Ramsundar AI4CE 37 389 0 19 Oct 2020
From Local Structures to Size Generalization in Graph Neural Networks Gilad Yehudai Ethan Fetaya E. Meirom Gal Chechik Haggai Maron GNN AI4CE 172 123 0 17 Oct 2020
MIMOSA: Multi-constraint Molecule Sampling for Molecule Optimization Tianfan Fu Cao Xiao Xinhao Li Lucas Glass Jimeng Sun 32 75 0 05 Oct 2020
How Neural Networks Extrapolate: From Feedforward to Graph Neural Networks Keyulu Xu Mozhi Zhang Jingling Li S. Du Ken-ichi Kawarabayashi Stefanie Jegelka MLT 25 306 0 24 Sep 2020
Transfer Learning of Graph Neural Networks with Ego-graph Information Maximization Qi Zhu Carl Yang Yidan Xu Haonan Wang Chao Zhang Jiawei Han 48 117 0 11 Sep 2020
Cross-lingual Semantic Role Labeling with Model Transfer Hao Fei Meishan Zhang Fei Li Donghong Ji 26 33 0 24 Aug 2020
Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs Dasol Hwang Jinyoung Park Sunyoung Kwon KyungHyun Kim Jung-Woo Ha Hyunwoo J. Kim 44 67 0 16 Jul 2020
ASGN: An Active Semi-supervised Graph Neural Network for Molecular Property Prediction Zhong Hao Chengqiang Lu Zheyuan Hu Hongya Wang Zhenya Huang Qi Liu Enhong Chen Cheekong Lee 32 137 0 07 Jul 2020
Graph Clustering with Graph Neural Networks Anton Tsitsulin John Palowitch Bryan Perozzi Emmanuel Müller GNN AI4CE 34 259 0 30 Jun 2020
GPT-GNN: Generative Pre-Training of Graph Neural Networks Ziniu Hu Yuxiao Dong Kuansan Wang Kai-Wei Chang Yizhou Sun SSL AI4CE 18 549 0 27 Jun 2020
Hierarchical Inter-Message Passing for Learning on Molecular Graphs Matthias Fey Jan-Gin Yuen F. Weichert GNN 41 86 0 22 Jun 2020
Subgraph Neural Networks Emily Alsentzer S. G. Finlayson Michelle M. Li Marinka Zitnik GNN 29 134 0 18 Jun 2020
Self-Supervised Graph Transformer on Large-Scale Molecular Data Yu Rong Yatao Bian Tingyang Xu Wei-yang Xie Ying Wei Wenbing Huang Junzhou Huang AI4CE 24 25 0 18 Jun 2020
Self-supervised Learning: Generative or Contrastive Xiao Liu Fanjin Zhang Zhenyu Hou Zhaoyu Wang Li Mian Jing Zhang Jie Tang SSL 52 1,587 0 15 Jun 2020
Graph Meta Learning via Local Subgraphs Kexin Huang Marinka Zitnik 42 161 0 14 Jun 2020
Open Graph Benchmark: Datasets for Machine Learning on Graphs Weihua Hu Matthias Fey Marinka Zitnik Yuxiao Dong Hongyu Ren Bowen Liu Michele Catasta J. Leskovec 61 2,663 0 02 May 2020
Autonomous discovery in the chemical sciences part II: Outlook Connor W. Coley Natalie S. Eyke K. Jensen 29 171 0 30 Mar 2020
A Survey of Deep Learning for Scientific Discovery M. Raghu Erica Schmidt OOD AI4CE 42 120 0 26 Mar 2020
A comprehensive study on the prediction reliability of graph neural networks for virtual screening Soojung Yang K. Lee Seongok Ryu 24 7 0 17 Mar 2020
Can Graph Neural Networks Count Substructures? Zhengdao Chen Lei Chen Soledad Villar Joan Bruna GNN 59 321 0 10 Feb 2020
A deep-learning view of chemical space designed to facilitate drug discovery P. Maragakis Hunter M. Nisonoff B. Cole D. Shaw 49 28 0 07 Feb 2020
Learning to Make Generalizable and Diverse Predictions for Retrosynthesis Benson Chen T. Shen Tommi Jaakkola Regina Barzilay 24 46 0 21 Oct 2019
Predicting materials properties without crystal structure: Deep representation learning from stoichiometry Rhys E. A. Goodall A. Lee 21 254 0 01 Oct 2019
InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization Fan-Yun Sun Jordan Hoffmann Vikas Verma Jian Tang SSL 50 844 0 31 Jul 2019
Graph Neural Networks: A Review of Methods and Applications Jie Zhou Yuchen Zhang Shengding Hu Zhengyan Zhang Cheng Yang Zhiyuan Liu Lifeng Wang Changcheng Li Maosong Sun AI4CE GNN 33 5,416 0 20 Dec 2018
Representation Learning on Graphs with Jumping Knowledge Networks Keyulu Xu Chengtao Li Yonglong Tian Tomohiro Sonobe Ken-ichi Kawarabayashi Stefanie Jegelka GNN 279 1,948 0 09 Jun 2018
Graph Convolutional Policy Network for Goal-Directed Molecular Graph Generation Jiaxuan You Bowen Liu Rex Ying Vijay S. Pande J. Leskovec GNN 215 886 0 07 Jun 2018
MoleculeNet: A Benchmark for Molecular Machine Learning Zhenqin Wu Bharath Ramsundar Evan N. Feinberg Joseph Gomes C. Geniesse Aneesh S. Pappu K. Leswing Vijay S. Pande OOD 260 1,787 0 02 Mar 2017