dgl

BP-Transformer: Modelling Long-Range Context via Binary Partitioning., Zihao Ye, Qipeng Guo, Quan Gan, Xipeng Qiu, Zheng Zhang

OptiMol: Optimization of Binding Affinities in Chemical Space for Drug Discovery, Jacques Boitreaud,Vincent Mallet, Carlos Oliver, Jérôme Waldispühl

JAKET: Joint Pre-training of Knowledge Graph and Language Understanding, Donghan Yu, Chenguang Zhu, Yiming Yang, Michael Zeng

Architectural Implications of Graph Neural Networks, Zhihui Zhang, Jingwen Leng, Lingxiao Ma, Youshan Miao, Chao Li, Minyi Guo

Combining Reinforcement Learning and Constraint Programming for Combinatorial Optimization, Quentin Cappart, Thierry Moisan, Louis-Martin Rousseau1, Isabeau Prémont-Schwarz, and Andre Cire

Therapeutics Data Commons: Machine Learning Datasets and Tasks for Therapeutics (code repo), Kexin Huang, Tianfan Fu, Wenhao Gao, Yue Zhao, Yusuf Roohani, Jure Leskovec, Connor W. Coley, Cao Xiao, Jimeng Sun, Marinka Zitnik

Sparse Graph Attention Networks, Yang Ye, Shihao Ji

On Self-Distilling Graph Neural Network, Yuzhao Chen, Yatao Bian, Xi Xiao, Yu Rong, Tingyang Xu, Junzhou Huang

Learning Robust Node Representations on Graphs, Xu Chen, Ya Zhang, Ivor Tsang, and Yuangang Pan

Recurrent Event Network: Autoregressive Structure Inference over Temporal Knowledge Graphs, Woojeong Jin, Meng Qu, Xisen Jin, Xiang Ren

Graph Neural Ordinary Differential Equations, Michael Poli, Stefano Massaroli, Junyoung Park, Atsushi Yamashita, Hajime Asama, Jinkyoo Park

FusedMM: A Unified SDDMM-SpMM Kernel for Graph Embedding and Graph Neural Networks, Md. Khaledur Rahman, Majedul Haque Sujon, , Ariful Azad

An Efficient Neighborhood-based Interaction Model for Recommendation on Heterogeneous Graph, KDD’20 Jiarui Jin, Jiarui Qin, Yuchen Fang, Kounianhua Du, Weinan Zhang, Yong Yu, Zheng Zhang, Alexander J. Smola

Learning Interaction Models of Structured Neighborhood on Heterogeneous Information Network, Jiarui Jin, Kounianhua Du, Weinan Zhang, Jiarui Qin, Yuchen Fang, Yong Yu, Zheng Zhang, Alexander J. Smola

Graphein - a Python Library for Geometric Deep Learning and Network Analysis on Protein Structures, Arian R. Jamasb, Pietro Lió, Tom L. Blundell

Graph Policy Gradients for Large Scale Robot Control, Arbaaz Khan, Ekaterina Tolstaya, Alejandro Ribeiro, Vijay Kumar

Heterogeneous Molecular Graph Neural Networks for Predicting Molecule Properties, Zeren Shui, George Karypis

Could Graph Neural Networks Learn Better Molecular Representation for Drug Discovery? A Comparison Study of Descriptor-based and Graph-based Models, Dejun Jiang, Zhenxing Wu, Chang-Yu Hsieh, Guangyong Chen, Ben Liao, Zhe Wang, Chao Shen, Dongsheng Cao, Jian Wu, Tingjun Hou

Principal Neighbourhood Aggregation for Graph Nets, Gabriele Corso, Luca Cavalleri, Dominique Beaini, Pietro Liò, Petar Veličković

Collective Multi-type Entity Alignment Between Knowledge Graphs, Qi Zhu, Hao Wei, Bunyamin Sisman, Da Zheng, Christos Faloutsos, Xin Luna Dong, Jiawei Han

Graph Representation Forecasting of Patient’s Medical Conditions: towards A Digital Twin, Pietro Barbiero, Ramon Viñas Torné, Pietro Lió

Relational Graph Learning on Visual and Kinematics Embeddings for Accurate Gesture Recognition in Robotic Surgery, Yong-Hao Long, Jie-Ying Wu, Bo Lu, Yue-Ming Jin, Mathias Unberath, Yun-Hui Liu, Pheng-Ann Heng and Qi Dou

Dark Reciprocal-Rank: Boosting Graph-Convolutional Self-Localization Network via Teacher-to-student Knowledge Transfer, Takeda Koji, Tanaka Kanji

Graph InfoClust: Leveraging Cluster-Level Node Information For Unsupervised Graph Representation Learning, Costas Mavromatis, George Karypis

GraphSeam: Supervised Graph Learning Framework for Semantic UV Mapping, Fatemeh Teimury, Bruno Roy, Juan Sebastian Casallas, David macdonald, Mark Coates

Comprehensive Study on Molecular Supervised Learning with Graph Neural Networks, Doyeong Hwang, Soojung Yang, Yongchan Kwon, Kyung Hoon Lee, Grace Lee, Hanseok Jo, Seyeol Yoon, and Seongok Ryu

A graph auto-encoder model for miRNA-disease associations prediction, Zhengwei Li, Jiashu Li, Ru Nie, Zhu-Hong You, Wenzheng Bao

Graph convolutional regression of cardiac depolarization from sparse endocardial maps, STACOM 2020 workshop, Felix Meister, Tiziano Passerini, Chloé Audigier, Èric Lluch, Viorel Mihalef, Hiroshi Ashikaga, Andreas Maier, Henry Halperin, Tommaso Mansi

AttnIO: Knowledge Graph Exploration with In-and-Out Attention Flow for Knowledge-Grounded Dialogue, EMNLP’20, Jaehun Jung, Bokyung Son, Sungwon Lyu

Learning from Non-Binary Constituency Trees via Tensor Decomposition, COLING’20, Daniele Castellana, Davide Bacciu

Inducing Alignment Structure with Gated Graph Attention Networks for Sentence Matching, Peng Cui, Le Hu, Yuanchao Liu

Enhancing Extractive Text Summarization with Topic-Aware Graph Neural Networks, COLING’20, Peng Cui, Le Hu, Yuanchao Liu

Double Graph Based Reasoning for Document-level Relation Extraction, EMNLP’20, Shuang Zeng, Runxin Xu, Baobao Chang, Lei Li

Systematic Generalization on gSCAN with Language Conditioned Embedding, AACL-IJCNLP’20, Tong Gao, Qi Huang, Raymond J. Mooney

Automatic selection of clustering algorithms using supervised graph embedding, Noy Cohen-Shapira, Lior Rokach

Improving Learning to Branch via Reinforcement Learning, Haoran Sun, Wenbo Chen, Hui Li, Le Song

A Practical Guide to Graph Neural Networks, Isaac Ronald Ward, Jack Joyner, Casey Lickfold, Stash Rowe, Yulan Guo, Mohammed Bennamoun, code

APAN: Asynchronous Propagation Attention Network for Real-time Temporal Graph Embedding, SIGMOD’21, Xuhong Wang, Ding Lyu, Mengjian Li, Yang Xia, Qi Yang, Xinwen Wang, Xinguang Wang, Ping Cui, Yupu Yang, Bowen Sun, Zhenyu Guo, Junkui Li

Uncertainty-Matching Graph Neural Networks to Defend Against Poisoning Attacks, Uday Shankar Shanthamallu, Jayaraman J. Thiagarajan, Andreas Spanias

Computing Graph Neural Networks: A Survey from Algorithms to Accelerators, Sergi Abadal, Akshay Jain, Robert Guirado, Jorge López-Alonso, Eduard Alarcón

NHK_STRL at WNUT-2020 Task 2: GATs with Syntactic Dependencies as Edges and CTC-based Loss for Text Classification, Yuki Yasuda, Taichi Ishiwatari, Taro Miyazaki, Jun Goto

Relation-aware Graph Attention Networks with Relational Position Encodings for Emotion Recognition in Conversations, Taichi Ishiwatari, Yuki Yasuda, Taro Miyazaki, Jun Goto

PGM-Explainer: Probabilistic Graphical Model Explanations for Graph Neural Networks, Minh N. Vu, My T. Thai

A Generalization of Transformer Networks to Graphs, Vijay Prakash Dwivedi, Xavier Bresson

Discourse-Aware Neural Extractive Text Summarization, ACL’20, Jiacheng Xu, Zhe Gan, Yu Cheng, Jingjing Liu

Learning Robust Node Representations on Graphs, Xu Chen, Ya Zhang, Ivor Tsang, Yuangang Pan

Adaptive Graph Diffusion Networks with Hop-wise Attention, Chuxiong Sun, Guoshi Wu

The Photoswitch Dataset: A Molecular Machine Learning Benchmark for the Advancement of Synthetic Chemistry, Aditya R. Thawani, Ryan-Rhys Griffiths, Arian Jamasb, Anthony Bourached, Penelope Jones, William McCorkindale, Alexander A. Aldrick, Alpha A. Lee

A community-powered search of machine learning strategy space to find NMR property prediction models, Lars A. Bratholm, Will Gerrard, Brandon Anderson, Shaojie Bai, Sunghwan Choi, Lam Dang, Pavel Hanchar, Addison Howard, Guillaume Huard, Sanghoon Kim, Zico Kolter, Risi Kondor, Mordechai Kornbluth, Youhan Lee, Youngsoo Lee, Jonathan P. Mailoa, Thanh Tu Nguyen, Milos Popovic, Goran Rakocevic, Walter Reade, Wonho Song, Luka Stojanovic, Erik H. Thiede, Nebojsa Tijanic, Andres Torrubia, Devin Willmott, Craig P. Butts, David R. Glowacki, Kaggle participants

Adaptive Layout Decomposition with Graph Embedding Neural Networks, Wei Li, Jialu Xia, Yuzhe Ma, Jialu Li, Yibo Lin, Bei Yu, DAC’20

Transfer Learning with Graph Neural Networks for Optoelectronic Properties of Conjugated Oligomers, J. Chem. Phys. 154, Chee-Kong Lee, Chengqiang Lu, Yue Yu, Qiming Sun, Chang-Yu Hsieh, Shengyu Zhang, Qi Liu, and Liang Shi

Jet tagging in the Lund plane with graph networks, Journal of High Energy Physics 2021, Frédéric A. Dreyer and Huilin Qu

Global Attention Improves Graph Networks Generalization, Omri Puny, Heli Ben-Hamu, and Yaron Lipman

Learning over Families of Sets – Hypergraph Representation Learning for Higher Order Tasks, SDM 2021, Balasubramaniam Srinivasan, Da Zheng, and George Karypis

SSFG: Stochastically Scaling Features and Gradients for Regularizing Graph Convolution Networks, Haimin Zhang, Min Xu

Application and evaluation of knowledge graph embeddings in biomedical data, PeerJ Computer Science 7:e341, Mona Alshahrani​, Maha A. Thafar, Magbubah Essack

MoTSE: an interpretable task similarity estimator for small molecular property prediction tasks, bioRxiv 2021.01.13.426608, Han Li, Xinyi Zhao, Shuya Li, Fangping Wan, Dan Zhao, Jianyang Zeng

Reinforcement Learning For Data Poisoning on Graph Neural Networks, Jacob Dineen, A S M Ahsan-Ul Haque, Matthew Bielskas

Generalising Recursive Neural Models by Tensor Decomposition, IJCNN’20, Daniele Castellana, Davide Bacciu

Tensor Decompositions in Recursive Neural Networks for Tree-Structured Data, ESANN’20, Daniele Castellana, Davide Bacciu

Combining Self-Organizing and Graph Neural Networks for Modeling Deformable Objects in Robotic Manipulation, Frotiers in Robotics and AI, Valencia, Angel J., and Pierre Payeur

Joint stroke classification and text line grouping in online handwritten documents with edge pooling attention networks, Pattern Recognition, Jun-Yu Ye, Yan-Ming Zhang, Qing Yang, Cheng-Lin Liu

Toward Accurate Predictions of Atomic Properties via Quantum Mechanics Descriptors Augmented Graph Convolutional Neural Network: Application of This Novel Approach in NMR Chemical Shifts Predictions, The Journal of Physical Chemistry Letters, Peng Gao, Jie Zhang, Yuzhu Sun, and Jianguo Yu

A Graph Neural Network to Model User Comfort in Robot Navigation, Pilar Bachiller, Daniel Rodriguez-Criado, Ronit R. Jorvekar, Pablo Bustos, Diego R. Faria, Luis J. Manso

Medical Entity Disambiguation Using Graph Neural Networks, Alina Vretinaris, Chuan Lei, Vasilis Efthymiou, Xiao Qin, Fatma Özcan

Chemistry-informed Macromolecule Graph Representation for Similarity Computation and Supervised Learning, Somesh Mohapatra, Joyce An, Rafael Gómez-Bombarelli

Characterizing and Forecasting User Engagement with In-app Action Graph: A Case Study of Snapchat, Yozen Liu, Xiaolin Shi, Lucas Pierce, Xiang Ren

GIPA: General Information Propagation Algorithm for Graph Learning, Qinkai Zheng, Houyi Li, Peng Zhang, Zhixiong Yang, Guowei Zhang, Xintan Zeng, Yongchao Liu

Graph Ensemble Learning over Multiple Dependency Trees for Aspect-level Sentiment Classification, NAACL’21, Xiaochen Hou, Peng Qi, Guangtao Wang, Rex Ying, Jing Huang, Xiaodong He, Bowen Zhou

Enhancing Scientific Papers Summarization with Citation Graph, AAAI’21, Chenxin An, Ming Zhong, Yiran Chen, Danqing Wang, Xipeng Qiu, Xuanjing Huang

Improving Graph Representation Learning by Contrastive Regularization, Kaili Ma, Haochen Yang, Han Yang, Tatiana Jin, Pengfei Chen, Yongqiang Chen, Barakeel Fanseu Kamhoua, James Cheng

Extract the Knowledge of Graph Neural Networks and Go Beyond it: An Effective Knowledge Distillation Framework, WWW’21, Cheng Yang, Jiawei Liu, Chuan Shi

VIKING: Adversarial Attack on Network Embeddings via Supervised Network Poisoning, PAKDD’21, Viresh Gupta, Tanmoy Chakraborty

Knowledge Graph Embedding using Graph Convolutional Networks with Relation-Aware Attention, Nasrullah Sheikh, Xiao Qin, Berthold Reinwald, Christoph Miksovic, Thomas Gschwind, Paolo Scotton

SLAPS: Self-Supervision Improves Structure Learning for Graph Neural Networks, Bahare Fatemi, Layla El Asri, Seyed Mehran Kazemi

Finding Needles in Heterogeneous Haystacks, AAAI’21, Bijaya Adhikari, Liangyue Li, Nikhil Rao, Karthik Subbian

RetCL: A Selection-based Approach for Retrosynthesis via Contrastive Learning, IJCAI 2021, Hankook Lee, Sungsoo Ahn, Seung-Woo Seo, You Young Song, Eunho Yang, Sung-Ju Hwang, Jinwoo Shin

Accurate Prediction of Free Solvation Energy of Organic Molecules via Graph Attention Network and Message Passing Neural Network from Pairwise Atomistic Interactions, Ramin Ansari, Amirata Ghorbani

DIPS-Plus: The Enhanced Database of Interacting Protein Structures for Interface Prediction, Alex Morehead, Chen Chen, Ada Sedova, Jianlin Cheng

Coreference-Aware Dialogue Summarization, SIGDIAL’21, Zhengyuan Liu, Ke Shi, Nancy F. Chen

Document Structure aware Relational Graph Convolutional Networks for Ontology Population, arXiv, Abhay M Shalghar, Ayush Kumar, Balaji Ganesan, Aswin Kannan, Shobha G

Covid-19 Detection from Chest X-ray and Patient Metadata using Graph Convolutional Neural Networks, Thosini Bamunu Mudiyanselage, Nipuna Senanayake, Chunyan Ji, Yi Pan, Yanqing Zhang

Rossmann-toolbox: a deep learning-based protocol for the prediction and design of cofactor specificity in Rossmann fold proteins, Briefings in Bioinformatics, Kamil Kaminski, Jan Ludwiczak, Maciej Jasinski, Adriana Bukala, Rafal Madaj, Krzysztof Szczepaniak, Stanislaw Dunin-Horkawicz

LGESQL: Line Graph Enhanced Text-to-SQL Model with Mixed Local and Non-Local Relations, ACL’21, Ruisheng Cao, Lu Chen, Zhi Chen, Yanbin Zhao, Su Zhu, Kai Yu

Enhancing Graph Neural Networks via auxiliary training for semi-supervised node classification, Knowledge-Based System’21, Yao Wu, Yu Song, Hong Huang, Fanghua Ye, Xing Xie, Hai Jin

Modeling Graph Node Correlations with Neighbor Mixture Models, Linfeng Liu, Michael C. Hughes, Li-Ping Liu

COMBINING PHYSICS AND MACHINE LEARNING FOR NETWORK FLOW ESTIMATION, ICLR’21, Arlei Silva, Furkan Kocayusufoglu, Saber Jafarpour, Francesco Bullo, Ananthram Swami, Ambuj Singh

A Classification Method for Academic Resources Based on a Graph Attention Network, Future Internet’21, Jie Yu, Yaliu Li, Chenle Pan and Junwei Wang

Large Graph Convolutional Network Training with GPU-Oriented Data Communication Architecture, Seung Won Min, Kun Wu, Sitao Huang, Mert Hidayetoğlu, Jinjun Xiong, Eiman Ebrahimi, Deming Chen, Wen-mei Hwu

Graph Attention Multi-Layer Perception, Wentao Zhang, Ziqi Yin, Zeang Sheng, Wen Ouyang, Xiaosen Li, Yangyu Tao, Zhi Yang, Bin Cui

GNNLens: A Visual Analytics Approach for Prediction Error Diagnosis of Graph Neural Networks, Zhihua Jin, Yong Wang, Qianwen Wang, Yao Ming, Tengfei Ma, Huamin Qu

How Attentive are Graph Attention Networks?, Shaked Brody, Uri Alon, Eran Yahav, code

SCENE: Reasoning about Traffic Scenes using Heterogeneous Graph Neural Networks, Thomas Monninger*, Julian Schmidt*, Jan Rupprecht, David Raba, Julian Jordan, Daniel Frank, Steffen Staab, Klaus Dietmayer, code, *co-first authors