Ecosyste.ms: Awesome

An open API service indexing awesome lists of open source software.

https://github.com/DeepGraphLearning/LiteratureDL4Graph

A comprehensive collection of recent papers on graph deep learning
https://github.com/DeepGraphLearning/LiteratureDL4Graph

arxiv deep-learning machine-learning papers

Last synced: 12 days ago
JSON representation

A comprehensive collection of recent papers on graph deep learning

Lists

README 

        
Literature of Deep Learning for Graphs

**************************************



This is a paper list about deep learning for graphs.



.. raw:: html



    
Sort by topic


    
Sort by venue



.. contents::

    :local:

    :depth: 2



.. sectnum::

    :depth: 2



.. role:: authors(emphasis)



.. role:: venue(strong)



.. role:: keywords(emphasis)



Node Representation Learning

============================



Unsupervised Node Representation Learning

-----------------------------------------



`DeepWalk: Online Learning of Social Representations

`_

    | :authors:`Bryan Perozzi, Rami Al-Rfou, Steven Skiena`

    | :venue:`KDD 2014`

    | :keywords:`Node classification, Random walk, Skip-gram`



`LINE: Large-scale Information Network Embedding

`_

    | :authors:`Jian Tang, Meng Qu, Mingzhe Wang, Ming Zhang, Jun Yan, Qiaozhu Mei`

    | :venue:`WWW 2015`

    | :keywords:`First-order, Second-order, Node classification`



`GraRep: Learning Graph Representations with Global Structural Information

`_

    | :authors:`Shaosheng Cao, Wei Lu, Qiongkai Xu`

    | :venue:`CIKM 2015`

    | :keywords:`High-order, SVD`



`node2vec: Scalable Feature Learning for Networks

`_

    | :authors:`Aditya Grover, Jure Leskovec`

    | :venue:`KDD 2016`

    | :keywords:`Breadth-first Search, Depth-first Search, Node Classification, Link Prediction`



`Variational Graph Auto-Encoders

`_

    | :authors:`Thomas N. Kipf, Max Welling`

    | :venue:`arXiv 2016`



`Scalable Graph Embedding for Asymmetric Proximity

`_

    | :authors:`Chang Zhou, Yuqiong Liu, Xiaofei Liu, Zhongyi Liu, Jun Gao`

    | :venue:`AAAI 2017`



`Fast Network Embedding Enhancement via High Order Proximity Approximation

`_

    | :authors:`Cheng Yang, Maosong Sun, Zhiyuan Liu, Cunchao Tu`

    | :venue:`IJCAI 2017`



`struc2vec: Learning Node Representations from Structural Identity

`_

    | :authors:`Leonardo F. R. Ribeiro, Pedro H. P. Savarese, Daniel R. Figueiredo`

    | :venue:`KDD 2017`

    | :keywords:`Structural Identity`



`Poincaré Embeddings for Learning Hierarchical Representations

`_

    | :authors:`Maximilian Nickel, Douwe Kiela`

    | :venue:`NIPS 2017`



`VERSE: Versatile Graph Embeddings from Similarity Measures

`_

    | :authors:`Anton Tsitsulin, Davide Mottin, Panagiotis Karras, Emmanuel Müller`

    | :venue:`WWW 2018`



`Network Embedding as Matrix Factorization: Unifying DeepWalk, LINE, PTE, and node2vec

`_

    | :authors:`Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Kuansan Wang, Jie Tang`

    | :venue:`WSDM 2018`



`Learning Structural Node Embeddings via Diffusion Wavelets

`_

    | :authors:`Claire Donnat, Marinka Zitnik, David Hallac, Jure Leskovec`

    | :venue:`KDD 2018`



`Adversarial Network Embedding

`_

    | :authors:`Quanyu Dai, Qiang Li, Jian Tang, Dan Wang`

    | :venue:`AAAI 2018`



`GraphGAN: Graph Representation Learning with Generative Adversarial Nets

`_

    | :authors:`Hongwei Wang, Jia Wang, Jialin Wang, Miao Zhao, Weinan Zhang, Fuzheng Zhang, Xing Xie, Minyi Guo`

    | :venue:`AAAI 2018`



`A General View for Network Embedding as Matrix Factorization

`_

    | :authors:`Xin Liu, Tsuyoshi Murata, Kyoung-Sook Kim, Chatchawan Kotarasu, Chenyi Zhuang`

    | :venue:`WSDM 2019`



`Deep Graph Infomax

`_

    | :authors:`Petar Veličković, William Fedus, William L. Hamilton, Pietro Liò, Yoshua Bengio, R Devon Hjelm`

    | :venue:`ICLR 2019`



`NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization

`_

    | :authors:`Jiezhong Qiu, Yuxiao Dong, Hao Ma, Jian Li, Chi Wang, Kuansan Wang, Jie Tang`

    | :venue:`WWW 2019`



`Adversarial Training Methods for Network Embedding

`_

    | :authors:`Quanyu Dai, Xiao Shen, Liang Zhang, Qiang Li, Dan Wang`

    | :venue:`WWW 2019`



`vGraph: A Generative Model for Joint Community Detection and Node Representation Learning

`_

    | :authors:`Fan-Yun Sun, Meng Qu, Jordan Hoffmann, Chin-Wei Huang, Jian Tang`

    | :venue:`NeurIPS 2019`



`ProGAN: Network Embedding via Proximity Generative Adversarial Network

`_

    | :authors:`Hongchang Gao, Jian Pei, Heng Huang`

    | :venue:`KDD 2019`



`GraphZoom: A Multi-level Spectral Approach for Accurate and Scalable Graph Embedding

`_

	| :authors:`Chenhui Deng, Zhiqiang Zhao, Yongyu Wang, Zhiru Zhang, Zhuo Feng`

	| :venue:`ICLR 2020`



Node Representation Learning in Heterogeneous Graphs

----------------------------------------------------



`Learning Latent Representations of Nodes for Classifying in Heterogeneous Social Networks

`_

    | :authors:`Yann Jacob, Ludovic Denoyer, Patrick Gallinari`

    | :venue:`WSDM 2014`



`PTE: Predictive Text Embedding through Large-scale Heterogeneous Text Networks

`_

    | :authors:`Jian Tang, Meng Qu, Qiaozhu Mei`

    | :venue:`KDD 2015`

    | :keywords:`Text Embedding, Heterogeneous Text Graphs`



`Heterogeneous Network Embedding via Deep Architectures

`_

    | :authors:`Shiyu Chang, Wei Han, Jiliang Tang, Guo-Jun Qi, Charu C. Aggarwal, Thomas S. Huang`

    | :venue:`KDD 2015`



`Network Representation Learning with Rich Text Information

`_

    | :authors:`Cheng Yang, Zhiyuan Liu, Deli Zhao, Maosong Sun, Edward Chang`

    | :venue:`AAAI 2015`



`Max-Margin DeepWalk: Discriminative Learning of Network Representation

`_

    | :authors:`Cunchao Tu, Weicheng Zhang, Zhiyuan Liu, Maosong Sun`

    | :venue:`IJCAI 2016`



`metapath2vec: Scalable Representation Learning for Heterogeneous Networks

`_

    | :authors:`Yuxiao Dong, Nitesh V. Chawla, Ananthram Swami`

    | :venue:`KDD 2017`



`Meta-Path Guided Embedding for Similarity Search in Large-Scale Heterogeneous Information Networks

`_

    | :authors:`Jingbo Shang, Meng Qu, Jialu Liu, Lance M. Kaplan, Jiawei Han, Jian Peng`

    | :venue:`arXiv 2016`



`HIN2Vec: Explore Meta-paths in Heterogeneous Information Networks for Representation Learning

`_

    | :authors:`Tao-yang Fu, Wang-Chien Lee, Zhen Lei`

    | :venue:`CIKM 2017`



`An Attention-based Collaboration Framework for Multi-View Network Representation Learning

`_

    | :authors:`Meng Qu, Jian Tang, Jingbo Shang, Xiang Ren, Ming Zhang, Jiawei Han`

    | :venue:`CIKM 2017`



`Multi-view Clustering with Graph Embedding for Connectome Analysis

`_

    | :authors:`Guixiang Ma, Lifang He, Chun-Ta Lu, Weixiang Shao, Philip S. Yu, Alex D. Leow, Ann B. Ragin`

    | :venue:`CIKM 2017`



`Attributed Signed Network Embedding

`_

    | :authors:`Suhang Wang, Charu Aggarwal, Jiliang Tang, Huan Liu`

    | :venue:`CIKM 2017`



`CANE: Context-Aware Network Embedding for Relation Modeling

`_

    | :authors:`Cunchao Tu, Han Liu, Zhiyuan Liu, Maosong Sun`

    | :venue:`ACL 2017`



`PME: Projected Metric Embedding on Heterogeneous Networks for Link Prediction

`_

    | :authors:`Hongxu Chen, Hongzhi Yin, Weiqing Wang, Hao Wang, Quoc Viet Hung Nguyen, Xue Li`

    | :venue:`KDD 2018`



`BiNE: Bipartite Network Embedding

`_

    | :authors:`Ming Gao, Leihui Chen, Xiangnan He, Aoying Zhou`

    | :venue:`SIGIR 2018`



`StarSpace: Embed All The Things

`_

    | :authors:`Ledell Wu, Adam Fisch, Sumit Chopra, Keith Adams, Antoine Bordes, Jason Weston`

    | :venue:`AAAI 2018`



`Exploring Expert Cognition for Attributed Network Embedding

`_

    | :authors:`Xiao Huang, Qingquan Song, Jundong Li, Xia Hu`

    | :venue:`WSDM 2018`



`SHINE: Signed Heterogeneous Information Network Embedding for Sentiment Link Prediction

`_

    | :authors:`Hongwei Wang, Fuzheng Zhang, Min Hou, Xing Xie, Minyi Guo, Qi Liu`

    | :venue:`WSDM 2018`



`Multidimensional Network Embedding with Hierarchical Structures

`_

    | :authors:`Yao Ma, Zhaochun Ren, Ziheng Jiang, Jiliang Tang, Dawei Yin`

    | :venue:`WSDM 2018`



`Curriculum Learning for Heterogeneous Star Network Embedding via Deep Reinforcement Learning

`_

    | :authors:`Meng Qu, Jian Tang, Jiawei Han`

    | :venue:`WSDM 2018`



`Generative Adversarial Network based Heterogeneous Bibliographic Network Representation for Personalized Citation Recommendation

`_

    | :authors:`Xiaoyan Cai, Junwei Han, Libin Yang`

    | :venue:`AAAI 2018`



`ANRL: Attributed Network Representation Learning via Deep Neural Networks

`_

    | :authors:`Zhen Zhang, Hongxia Yang, Jiajun Bu, Sheng Zhou, Pinggang Yu, Jianwei Zhang, Martin Ester, Can Wang`

    | :venue:`IJCAI 2018`



`Efficient Attributed Network Embedding via Recursive Randomized Hashing

`_

    | :authors:`Wei Wu, Bin Li, Ling Chen, Chengqi Zhang`

    | :venue:`IJCAI 2018`



`Deep Attributed Network Embedding

`_

    | :authors:`Hongchang Gao, Heng Huang`

    | :venue:`IJCAI 2018`



`Co-Regularized Deep Multi-Network Embedding

`_

    | :authors:`Jingchao Ni, Shiyu Chang, Xiao Liu, Wei Cheng, Haifeng Chen, Dongkuan Xu, Xiang Zhang`

    | :venue:`WWW 2018`



`Easing Embedding Learning by Comprehensive Transcription of Heterogeneous Information Networks

`_

    | :authors:`Yu Shi, Qi Zhu, Fang Guo, Chao Zhang, Jiawei Han`

    | :venue:`KDD 2018`



`Meta-Graph Based HIN Spectral Embedding: Methods, Analyses, and Insights

`_

    | :authors:`Carl Yang, Yichen Feng, Pan Li, Yu Shi, Jiawei Han`

    | :venue:`ICDM 2018`



`SIDE: Representation Learning in Signed Directed Networks

`_

    | :authors:`Junghwan Kim, Haekyu Park, Ji-Eun Lee, U Kang`

    | :venue:`WWW 2018`



`Learning Network-to-Network Model for Content-rich Network Embedding

`_

    | :authors:`	Zhicheng He, Jie Liu, Na Li, Yalou Huang`

    | :venue:`KDD 2019`



Node Representation Learning in Dynamic Graphs

----------------------------------------------



`Know-evolve: Deep temporal reasoning for dynamic knowledge graphs

`_

    | :authors:`Rakshit Trivedi, Hanjun Dai, Yichen Wang, Le Song`

    | :venue:`ICML 2017`



`Dyngem: Deep embedding method for dynamic graphs

`_

    | :authors:`Palash Goyal, Nitin Kamra, Xinran He, Yan Liu`

    | :venue:`ICLR 2017 Workshop`



`Attributed network embedding for learning in a dynamic environment

`_

    | :authors:`Jundong Li, Harsh Dani, Xia Hu, Jiliang Tang, Yi Chang, Huan Liu`

    | :venue:`CIKM 2017`



`Dynamic Network Embedding by Modeling Triadic Closure Process

`_

    | :authors:`Lekui Zhou, Yang Yang, Xiang Ren, Fei Wu, Yueting Zhuang`

    | :venue:`AAAI 2018`



`DepthLGP: Learning Embeddings of Out-of-Sample Nodes in Dynamic Networks

`_

    | :authors:`Jianxin Ma, Peng Cui, Wenwu Zhu`

    | :venue:`AAAI 2018`



`TIMERS: Error-Bounded SVD Restart on Dynamic Networks

`_

    | :authors:`Ziwei Zhang, Peng Cui, Jian Pei, Xiao Wang, Wenwu Zhu`

    | :venue:`AAAI 2018`



`Dynamic Embeddings for User Profiling in Twitter

`_

    | :authors:`Shangsong Liang, Xiangliang Zhang, Zhaochun Ren, Evangelos Kanoulas`

    | :venue:`KDD 2018`



`Dynamic Network Embedding : An Extended Approach for Skip-gram based Network Embedding

`_

    | :authors:`Lun Du, Yun Wang, Guojie Song, Zhicong Lu, Junshan Wang`

    | :venue:`IJCAI 2018`



`DyRep: Learning Representations over Dynamic Graphs

`_

    | :authors:`Rakshit Trivedi, Mehrdad Farajtabar, Prasenjeet Biswal, Hongyuan Zha`

    | :venue:`ICLR 2019`



`Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks

`_

    | :authors:`Srijan Kumar, Xikun Zhang, Jure Leskovec`

    | :venue:`KDD 2019`



`Variational Graph Recurrent Neural Networks

`_

    | :authors:`Ehsan Hajiramezanali, Arman Hasanzadeh, Nick Duffield, Krishna R Narayanan, Mingyuan Zhou, Xiaoning Qian`

    | :venue:`NeurIPS 2019`



`Social-BiGAT: Multimodal Trajectory Forecasting using Bicycle-GAN and Graph Attention Networks

`_

    | :authors:`Vineet Kosaraju, Amir Sadeghian, Roberto Martín-Martín, Ian Reid, S. Hamid Rezatofighi, Silvio Savarese`

    | :venue:`NeurIPS 2019`



Knowledge Graph Embedding

=========================



`A Three-Way Model for Collective Learning on Multi-Relational Data.

`_

    | :authors:`Maximilian Nickel, Volker Tresp, Hans-Peter Kriegel`

    | :venue:`ICML 2011`



`Translating Embeddings for Modeling Multi-relational Data

`_

    | :authors:`Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, Oksana Yakhnenko`

    | :venue:`NIPS 2013`



`Knowledge Graph Embedding by Translating on Hyperplanes

`_

    | :authors:`Zhen Wang, Jianwen Zhang, Jianlin Feng, Zheng Chen`

    | :venue:`AAAI 2014`



`Reducing the Rank of Relational Factorization Models by Including Observable Patterns

`_

    | :authors:`Maximilian Nickel, Xueyan Jiang, Volker Tresp`

    | :venue:`NIPS 2014`



`Learning Entity and Relation Embeddings for Knowledge Graph Completion

`_

    | :authors:`Yankai Lin, Zhiyuan Liu, Maosong Sun, Yang Liu, Xuan Zhu`

    | :venue:`AAAI 2015`



`A Review of Relational Machine Learning for Knowledge Graph

`_

    | :authors:`Maximilian Nickel, Kevin Murphy, Volker Tresp, Evgeniy Gabrilovich`

    | :venue:`IEEE 2015`



`Knowledge Graph Embedding via Dynamic Mapping Matrix

`_

    | :authors:`Guoliang Ji, Shizhu He, Liheng Xu, Kang Liu, Jun Zha`

    | :venue:`ACL 2015`



`Modeling Relation Paths for Representation Learning of Knowledge Bases

`_

    | :authors:`Yankai Lin, Zhiyuan Liu, Huanbo Luan, Maosong Sun, Siwei Rao, Song Liu`

    | :venue:`EMNLP 2015`



`Embedding Entities and Relations for Learning and Inference in Knowledge Bases

`_

    | :authors:`Bishan Yang, Wen-tau Yih, Xiaodong He, Jianfeng Gao, Li Deng`

    | :venue:`ICLR 2015`



`Holographic Embeddings of Knowledge Graphs

`_

    | :authors:`Maximilian Nickel, Lorenzo Rosasco, Tomaso Poggio`

    | :venue:`AAAI 2016`



`Complex Embeddings for Simple Link Prediction

`_

    | :authors:`Théo Trouillon, Johannes Welbl, Sebastian Riedel, Éric Gaussier, Guillaume Bouchard`

    | :venue:`ICML 2016`



`Modeling Relational Data with Graph Convolutional Networks

`_

    | :authors:`Michael Schlichtkrull, Thomas N. Kipf, Peter Bloem, Rianne Van Den Berg, Ivan Titov, Max Welling`

    | :venue:`arXiv 2017`



`Fast Linear Model for Knowledge Graph Embeddings

`_

    | :authors:`Armand Joulin, Edouard Grave, Piotr Bojanowski, Maximilian Nickel, Tomas Mikolov`

    | :venue:`arXiv 2017`



`Convolutional 2D Knowledge Graph Embeddings

`_

    | :authors:`Tim Dettmers, Pasquale Minervini, Pontus Stenetorp, Sebastian Riedel`

    | :venue:`AAAI 2018`



`Knowledge Graph Embedding With Iterative Guidance From Soft Rules

`_

    | :authors:`Shu Guo, Quan Wang, Lihong Wang, Bin Wang, Li Guo`

    | :venue:`AAAI 2018`



`KBGAN: Adversarial Learning for Knowledge Graph Embeddings

`_

    | :authors:`Liwei Cai, William Yang Wang`

    | :venue:`NAACL 2018`



`Improving Knowledge Graph Embedding Using Simple Constraints

`_

    | :authors:`Boyang Ding, Quan Wang, Bin Wang, Li Guo`

    | :venue:`ACL 2018`



`SimplE Embedding for Link Prediction in Knowledge Graphs

`_

    | :authors:`Seyed Mehran Kazemi, David Poole`

    | :venue:`NeurIPS 2018`



`A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network

`_

    | :authors:`Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Phung`

    | :venue:`NAACL 2018`



`Iteratively Learning Embeddings and Rules for Knowledge Graph Reasoning

`_

    | :authors:`Wen Zhang, Bibek Paudel, Liang Wang, Jiaoyan Chen, Hai Zhu, Wei Zhang, Abraham Bernstein, Huajun Chen`

    | :venue:`WWW 2019`



`RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space

`_

    | :authors:`Zhiqing Sun, Zhi-Hong Deng, Jian-Yun Nie, Jian Tang`

    | :venue:`ICLR 2019`



`Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs

`_

    | :authors:`Deepak Nathani, Jatin Chauhan, Charu Sharma, Manohar Kaul`

    | :venue:`ACL 2019`



`Probabilistic Logic Neural Networks for Reasoning

`_

    | :authors:`Meng Qu, Jian Tang`

    | :venue:`NeurIPS 2019`



`Quaternion Knowledge Graph Embeddings

`_

    | :authors:`Shuai Zhang, Yi Tay, Lina Yao, Qi Liu`

    | :venue:`NeurIPS 2019`



`Quantum Embedding of Knowledge for Reasoning

`_

	| :authors:`Dinesh Garg, Santosh K. Srivastava, Hima Karanam`

	| :venue:`NeurIPS 2019`

	

`Multi-relational Poincaré Graph Embeddings

`_

    | :authors:`Ivana Balaževic, Carl Allen, Timothy Hospedales`

    | :venue:`NeurIPS 2019`



`Dynamically Pruned Message Passing Networks for Large-scale Knowledge Graph Reasoning

`_

	| :authors:`Xiaoran Xu, Wei Feng, Yunsheng Jiang, Xiaohui Xie, Zhiqing Sun, Zhi-Hong Deng`

	| :venue:`ICLR 2020`

	

Graph Neural Networks

=====================



`Revisiting Semi-supervised Learning with Graph Embeddings

`_

    | :authors:`Zhilin Yang, William W. Cohen, Ruslan Salakhutdinov`

    | :venue:`ICML 2016`



`Semi-Supervised Classification with Graph Convolutional Networks

`_

    | :authors:`Thomas N. Kipf, Max Welling`

    | :venue:`ICLR 2017`



`Neural Message Passing for Quantum Chemistry

`_

    | :authors:`Justin Gilmer, Samuel S. Schoenholz, Patrick F. Riley, Oriol Vinyals, George E. Dahl`

    | :venue:`ICML 2017`



`Motif-Aware Graph Embeddings

`_

    | :authors:`Hoang Nguyen, Tsuyoshi Murata`

    | :venue:`IJCAI 2017`



`Learning Graph Representations with Embedding Propagation

`_

    | :authors:`Alberto Garcia-Duran, Mathias Niepert`

    | :venue:`NIPS 2017`



`Inductive Representation Learning on Large Graphs

`_

    | :authors:`William L. Hamilton, Rex Ying, Jure Leskovec`

    | :venue:`NIPS 2017`



`Graph Attention Networks

`_

    | :authors:`Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, Yoshua Bengio`

    | :venue:`ICLR 2018`



`FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling

`_

    | :authors:`Jie Chen, Tengfei Ma, Cao Xiao`

    | :venue:`ICLR 2018`



`Representation Learning on Graphs with Jumping Knowledge Networks

`_

    | :authors:`Keyulu Xu, Chengtao Li, Yonglong Tian, Tomohiro Sonobe, Ken-ichi Kawarabayashi, Stefanie Jegelka`

    | :venue:`ICML 2018`



`Stochastic Training of Graph Convolutional Networks with Variance Reduction

`_

    | :authors:`Jianfei Chen, Jun Zhu, Le Song`

    | :venue:`ICML 2018`



`Large-Scale Learnable Graph Convolutional Networks

`_

    | :authors:`Hongyang Gao, Zhengyang Wang, Shuiwang Ji`

    | :venue:`KDD 2018`



`Adaptive Sampling Towards Fast Graph Representation Learning

`_

    | :authors:`Wenbing Huang, Tong Zhang, Yu Rong, Junzhou Huang`

    | :venue:`NeurIPS 2018`



`Hierarchical Graph Representation Learning with Differentiable Pooling

`_

    | :authors:`Rex Ying, Jiaxuan You, Christopher Morris, Xiang Ren, William L. Hamilton, Jure Leskovec`

    | :venue:`NeurIPS 2018`



`Bayesian Semi-supervised Learning with Graph Gaussian Processes

`_

    | :authors:`Yin Cheng Ng, Nicolò Colombo, Ricardo Silva`

    | :venue:`NeurIPS 2018`



`Pitfalls of Graph Neural Network Evaluation

`_

    | :authors:`Oleksandr Shchur, Maximilian Mumme, Aleksandar Bojchevski, Stephan Günnemann`

    | :venue:`arXiv 2018`



`Heterogeneous Graph Attention Network

`_

    | :authors:`Xiao Wang, Houye Ji, Chuan Shi, Bai Wang, Peng Cui, P. Yu, Yanfang Ye`

    | :venue:`WWW 2019`



`Bayesian graph convolutional neural networks for semi-supervised classification

`_

    | :authors:`Yingxue Zhang, Soumyasundar Pal, Mark Coates, Deniz Üstebay`

    | :venue:`AAAI 2019`



`How Powerful are Graph Neural Networks?

`_

    | :authors:`Keyulu Xu, Weihua Hu, Jure Leskovec, Stefanie Jegelka`

    | :venue:`ICLR 2019`



`LanczosNet: Multi-Scale Deep Graph Convolutional Networks

`_

    | :authors:`Renjie Liao, Zhizhen Zhao, Raquel Urtasun, Richard S. Zemel`

    | :venue:`ICLR 2019`



`Graph Wavelet Neural Network

`_

    | :authors:`Bingbing Xu, Huawei Shen, Qi Cao, Yunqi Qiu, Xueqi Cheng`

    | :venue:`ICLR 2019`



`Supervised Community Detection with Line Graph Neural Networks

`_

    | :authors:`Zhengdao Chen, Xiang Li, Joan Bruna`

    | :venue:`ICLR 2019`



`Predict then Propagate: Graph Neural Networks meet Personalized PageRank

`_

    | :authors:`Johannes Klicpera, Aleksandar Bojchevski, Stephan Günnemann`

    | :venue:`ICLR 2019`



`Invariant and Equivariant Graph Networks

`_

    | :authors:`Haggai Maron, Heli Ben-Hamu, Nadav Shamir, Yaron Lipman`

    | :venue:`ICLR 2019`



`Capsule Graph Neural Network

`_

    | :authors:`Zhang Xinyi, Lihui Chen`

    | :venue:`ICLR 2019`



`MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing

`_

    | :authors:`Sami Abu-El-Haija, Bryan Perozzi, Amol Kapoor, Nazanin Alipourfard, Kristina Lerman, Hrayr Harutyunyan, Greg Ver Steeg, Aram Galstyan`

    | :venue:`ICML 2019`



`Graph U-Nets

`_

    | :authors:`Hongyang Gao, Shuiwang Ji`

    | :venue:`ICML 2019`



`Disentangled Graph Convolutional Networks

`_

    | :authors:`Jianxin Ma, Peng Cui, Kun Kuang, Xin Wang, Wenwu Zhu`

    | :venue:`ICML 2019`



`GMNN: Graph Markov Neural Networks

`_

    | :authors:`Meng Qu, Yoshua Bengio, Jian Tang`

    | :venue:`ICML 2019`



`Simplifying Graph Convolutional Networks

`_

    | :authors:`Felix Wu, Tianyi Zhang, Amauri Holanda de Souza Jr., Christopher Fifty, Tao Yu, Kilian Q. Weinberger`

    | :venue:`ICML 2019`



`Position-aware Graph Neural Networks

`_

    | :authors:`Jiaxuan You, Rex Ying, Jure Leskovec`

    | :venue:`ICML 2019`



`Self-Attention Graph Pooling

`_

    | :authors:`Junhyun Lee, Inyeop Lee, Jaewoo Kang`

    | :venue:`ICML 2019`



`Relational Pooling for Graph Representations

`_

    | :authors:`Ryan L. Murphy, Balasubramaniam Srinivasan, Vinayak Rao, Bruno Ribeiro`

    | :venue:`ICML 2019`



`Graph Representation Learning via Hard and Channel-Wise Attention Networks

`_

    | :authors:`Hongyang Gao, Shuiwang Ji`

    | :venue:`KDD 2019`



`Conditional Random Field Enhanced Graph Convolutional Neural Networks

`_

    | :authors:`Hongchang Gao, Jian Pei, Heng Huang`

    | :venue:`KDD 2019`



`Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks

`_

    | :authors:`Wei-Lin Chiang, Xuanqing Liu, Si Si, Yang Li, Samy Bengio, Cho-Jui Hsieh`

    | :venue:`KDD 2019`



`DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification

`_

    | :authors:`Jun Wu, Jingrui He, Jiejun Xu`

    | :venue:`KDD 2019`



`HetGNN: Heterogeneous Graph Neural Network

`_

    | :authors:`Chuxu Zhang, Dongjin Song, Chao Huang, Ananthram Swami, Nitesh V. Chawla`

    | :venue:`KDD 2019`



`Graph Recurrent Networks with Attributed Random Walks

`_

    | :authors:`Xiao Huang, Qingquan Song, Yuening Li, Xia Hu`

    | :venue:`KDD 2019`



`Graph Convolutional Networks with EigenPooling

`_

    | :authors:`Yao Ma, Suhang Wang, Charu Aggarwal, Jiliang Tang`

    | :venue:`KDD 2019`



`DFNets: Spectral CNNs for Graphs with Feedback-Looped Filters

`_

    | :authors:`Asiri Wijesinghe, Qing Wang`

    | :venue:`NeurIPS 2019`



`Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology

`_

    | :authors:`Nima Dehmamy, Albert-László Barabási, Rose Yu`

    | :venue:`NeurIPS 2019`



`A Flexible Generative Framework for Graph-based Semi-supervised Learning

`_

    | :authors:`Jiaqi Ma, Weijing Tang, Ji Zhu, Qiaozhu Mei`

    | :venue:`NeurIPS 2019`



`Rethinking Kernel Methods for Node Representation Learning on Graphs

`_

    | :authors:`Yu Tian, Long Zhao, Xi Peng, Dimitris N. Metaxas`

    | :venue:`NeurIPS 2019`



`Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks

`_

    | :authors:`Sitao Luan, Mingde Zhao, Xiao-Wen Chang, Doina Precup`

    | :venue:`NeurIPS 2019`



`N-Gram Graph: A Simple Unsupervised Representation for Molecules

`_

    | :authors:`Shengchao Liu, Thevaa Chandereng, Yingyu Liang`

    | :venue:`NeurIPS 2019`



`DeepGCNs: Can GCNs Go as Deep as CNNs?

`_

    | :authors:`Guohao Li, Matthias Muller, Ali Thabet, Bernard Ghanem`

    | :venue:`ICCV 2019`



`Continuous Graph Neural Networks

`_

    | :authors:`Louis-Pascal A. C. Xhonneux, Meng Qu, Jian Tang`

    | :venue:`arXiv 2019`



`Curvature Graph Network

`_

	| :authors:`Ze Ye, Kin Sum Liu, Tengfei Ma, Jie Gao, Chao Chen`

	| :venue:`ICLR 2020`



`Memory-based Graph Networks

`_

	| :authors:`Amir hosein Khasahmadi, Kaveh Hassani, Parsa Moradi, Leo Lee, Quaid Morris`

	| :venue:`ICLR 2020`

	

`Strategies for Pre-training Graph Neural Networks

`_

	| :authors:`Weihua Hu, Bowen Liu, Joseph Gomes, Marinka Zitnik, Percy Liang, Vijay Pande, Jure Leskovec`

	| :venue:`ICLR 2020`



Applications of Graph Deep Learning

=================================



Natural Language Processing

---------------------------



`Encoding Sentences with Graph Convolutional Networks for Semantic Role Labeling

`_

    | :authors:`Diego Marcheggiani, Ivan Titov`

    | :venue:`EMNLP 2017`



`Graph Convolutional Encoders for Syntax-aware Neural Machine Translation

`_

    | :authors:`Joost Bastings, Ivan Titov, Wilker Aziz, Diego Marcheggiani, Khalil Sima’an`

    | :venue:`EMNLP 2017`



`Graph-based Neural Multi-Document Summarization

`_

    | :authors:`Michihiro Yasunaga, Rui Zhang, Kshitijh Meelu, Ayush Pareek, Krishnan Srinivasan, Dragomir Radev`

    | :venue:`CoNLL 2017`



`QANet: Combining Local Convolution with Global Self-Attention for Reading Comprehension

`_

    | :authors:`Adams Wei Yu, David Dohan, Minh-Thang Luong, Rui Zhao, Kai Chen, Mohammad Norouzi, Quoc V. Le`

    | :venue:`ICLR 2018`



`A Structured Self-attentive Sentence Embedding

`_

    | :authors:`Zhouhan Lin, Minwei Feng, Cicero Nogueira dos Santos, Mo Yu, Bing Xiang, Bowen Zhou, Yoshua Bengio`

    | :venue:`ICLR 2018`



`Modeling Semantics with Gated Graph Neural Networks for Knowledge Base Question Answering

`_

    | :authors:`Daniil Sorokin, Iryna Gurevych`

    | :venue:`COLING 2018`



`Exploiting Semantics in Neural Machine Translation with Graph Convolutional Networks

`_

    | :authors:`Diego Marcheggiani, Joost Bastings, Ivan Titov`

    | :venue:`NAACL 2018`



`Linguistically-Informed Self-Attention for Semantic Role Labeling

`_

    | :authors:`Emma Strubell, Patrick Verga, Daniel Andor, David Weiss, Andrew McCallum`

    | :venue:`EMNLP 2018`



`Graph Convolution over Pruned Dependency Trees Improves Relation Extraction

`_

    | :authors:`Yuhao Zhang, Peng Qi, Christopher D. Manning`

    | :venue:`EMNLP 2018`



`A Graph-to-Sequence Model for AMR-to-Text Generation

`_

    | :authors:`Linfeng Song, Yue Zhang, Zhiguo Wang, Daniel Gildea`

    | :venue:`ACL 2018`



`Graph-to-Sequence Learning using Gated Graph Neural Networks

`_

    | :authors:`Daniel Beck, Gholamreza Haffari, Trevor Cohn`

    | :venue:`ACL 2018`



`Graph Convolutional Networks for Text Classification

`_

    | :authors:`Liang Yao, Chengsheng Mao, Yuan Luo`

    | :venue:`AAAI 2019`



`Differentiable Perturb-and-Parse: Semi-Supervised Parsing with a Structured Variational Autoencoder

`_

    | :authors:`Caio Corro, Ivan Titov`

    | :venue:`ICLR 2019`



`Structured Neural Summarization

`_

    | :authors:`Patrick Fernandes, Miltiadis Allamanis, Marc Brockschmid`

    | :venue:`ICLR 2019`



`Multi-task Learning over Graph Structures

`_

    | :authors:`Pengfei Liu, Jie Fu, Yue Dong, Xipeng Qiu, Jackie Chi Kit Cheung`

    | :venue:`AAAI 2019`



`Imposing Label-Relational Inductive Bias for Extremely Fine-Grained Entity Typing

`_

    | :authors:`Wenhan Xiong, Jiawei Wu, Deren Lei, Mo Yu, Shiyu Chang, Xiaoxiao Guo, William Yang Wang`

    | :venue:`NAACL 2019`



`Single Document Summarization as Tree Induction

`_

    | :authors:`Yang Liu, Ivan Titov, Mirella Lapata`

    | :venue:`NAACL 2019`



`Long-tail Relation Extraction via Knowledge Graph Embeddings and Graph Convolution Networks

`_

    | :authors:`Ningyu Zhang, Shumin Deng, Zhanlin Sun, Guanying Wang, Xi Chen, Wei Zhang, Huajun Chen`

    | :venue:`NAACL 2019`



`Graph Neural Networks with Generated Parameters for Relation Extraction

`_

    | :authors:`Hao Zhu, Yankai Lin, Zhiyuan Liu, Jie Fu, Tat-seng Chua, Maosong Sun`

    | :venue:`ACL 2019`



`Dynamically Fused Graph Network for Multi-hop Reasoning

`_

    | :authors:`Yunxuan Xiao, Yanru Qu, Lin Qiu, Hao Zhou, Lei Li, Weinan Zhang, Yong Yu`

    | :venue:`ACL 2019`



`Encoding Social Information with Graph Convolutional Networks for Political Perspective Detection

in News Media

`_

    | :authors:`Chang Li, Dan Goldwasser`

    | :venue:`ACL 2019`



`Attention Guided Graph Convolutional Networks for Relation Extraction

`_

    | :authors:`Zhijiang Guo, Yan Zhang, Wei Lu`

    | :venue:`ACL 2019`



`Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks

`_

    | :authors:`Shikhar Vashishth, Manik Bhandari, Prateek Yadav, Piyush Rai, Chiranjib Bhattacharyya, Partha Talukdar`

    | :venue:`ACL 2019`



`GraphRel: Modeling Text as Relational Graphs for Joint Entity and Relation Extraction

`_

    | :authors:`Tsu-Jui Fu, Peng-Hsuan Li, Wei-Yun Ma`

    | :venue:`ACL 2019`



`Multi-hop Reading Comprehension across Multiple Documents by Reasoning over Heterogeneous Graphs

`_

    | :authors:`Ming Tu, Guangtao Wang, Jing Huang, Yun Tang, Xiaodong He, Bowen Zhou`

    | :venue:`ACL 2019`



`Cognitive Graph for Multi-Hop Reading Comprehension at Scale

`_

    | :authors:`Ming Ding, Chang Zhou, Qibin Chen, Hongxia Yang, Jie Tang`

    | :venue:`ACL 2019`



`Coherent Comment Generation for Chinese Articles with a Graph-to-Sequence Model

`_

    | :authors:`Wei Li, Jingjing Xu, Yancheng He, Shengli Yan, Yunfang Wu, Xu Sun`

    | :venue:`ACL 2019`



`Matching Article Pairs with Graphical Decomposition and Convolutions

`_

    | :authors:`Bang Liu, Di Niu, Haojie Wei, Jinghong Lin, Yancheng He, Kunfeng Lai, Yu Xu`

    | :venue:`ACL 2019`



`Embedding Imputation with Grounded Language Information

`_

    | :authors:`Ziyi Yang, Chenguang Zhu, Vin Sachidananda, Eric Darve`

    | :venue:`ACL 2019`



`Encoding Social Information with Graph Convolutional Networks forPolitical Perspective Detection in News Media

`_

    | :authors:`Chang Li, Dan Goldwasser`

    | :venue:`ACL 2019`



`A Neural Multi-digraph Model for Chinese NER with Gazetteers

`_

    | :authors:`Ruixue Ding, Pengjun Xie, Xiaoyan Zhang, Wei Lu, Linlin Li, Luo Si`

    | :venue:`ACL 2019`



`Tree Communication Models for Sentiment Analysis

`_

    | :authors:`Yuan Zhang, Yue Zhang`

    | :venue:`ACL 2019`



`A2N: Attending to Neighbors for Knowledge Graph Inference

`_

    | :authors:`Trapit Bansal, Da-Cheng Juan, Sujith Ravi, Andrew McCallum`

    | :venue:`ACL 2019`



`Textbook Question Answering with Multi-modal Context Graph Understanding and Self-supervised Open-set Comprehension

`_

    | :authors:`Daesik Kim, Seonhoon Kim, Nojun Kwak`

    | :venue:`ACL 2019`



`Look Again at the Syntax: Relational Graph Convolutional Network for Gendered Ambiguous Pronoun Resolution

`_

    | :authors:`Yinchuan Xu, Junlin Yang`

    | :venue:`ACL 2019 Workshop`

    | :keywords:`https://github.com/ianycxu/RGCN-with-BERT`



`Learning Graph Pooling and Hybrid Convolutional Operations for Text Representations

`_

    | :authors:`Hongyang Gao, Yongjun Chen, Shuiwang Ji`

    | :venue:`WWW 2019`



`Learning to Create Sentence Semantic Relation Graphs for Multi-Document Summarization

`_

    | :authors:`Diego Antognini, Boi Faltings`

    | :venue:`EMNLP 2019`



`Dependency-Guided LSTM-CRF for Named Entity Recognition

`_

    | :authors:`Zhanming Jie, Wei Lu`

    | :venue:`EMNLP 2019`



`Modeling Conversation Structure and Temporal Dynamics for Jointly Predicting Rumor Stance and Veracity

`_

    | :authors:`Penghui Wei, Nan Xu, Wenji Mao`

    | :venue:`EMNLP 2019`



`DialogueGCN: A Graph Convolutional Neural Network for Emotion Recognition in Conversation

`_

    | :authors:`Deepanway Ghosal, Navonil Majumder, Soujanya Poria, Niyati Chhaya, Alexander Gelbukh`

    | :venue:`EMNLP 2019`



`Modeling Graph Structure in Transformer for Better AMR-to-Text Generation

`_

    | :authors:`Jie Zhu, Junhui Li, Muhua Zhu, Longhua Qian, Min Zhang, Guodong Zhou`

    | :venue:`EMNLP 2019`



`KagNet: Knowledge-Aware Graph Networks for Commonsense Reasoning

`_

    | :authors:`Bill Yuchen Lin, Xinyue Chen, Jamin Chen, Xiang Ren`

    | :venue:`EMNLP 2019`



Computer Vision

---------------



`3D Graph Neural Networks for RGBD Semantic Segmentation

`_

    | :authors:`Xiaojuan Qi, Renjie Liao, Jiaya Jia, Sanja Fidler, Raquel Urtasun`

    | :venue:`ICCV 2017`



`Situation Recognition With Graph Neural Networks

`_

    | :authors:`Ruiyu Li, Makarand Tapaswi, Renjie Liao, Jiaya Jia, Raquel Urtasun, Sanja Fidler`

    | :venue:`ICCV 2017`



`Graph-Based Classification of Omnidirectional Images

`_

    | :authors:`Renata Khasanova, Pascal Frossard`

    | :venue:`ICCV 2017`



`Spatial Temporal Graph Convolutional Networks for Skeleton-Based Action Recognition

`_

    | :authors:`Sijie Yan, Yuanjun Xiong, Dahua Lin`

    | :venue:`AAAI 2018`



`Image Generation from Scene Graphs

`_

    | :authors:`Justin Johnson, Agrim Gupta, Li Fei-Fei`

    | :venue:`CVPR 2018`



`FoldingNet: Point Cloud Auto-Encoder via Deep Grid Deformation

`_

    | :authors:`Yaoqing Yang, Chen Feng, Yiru Shen, Dong Tian`

    | :venue:`CVPR 2018`



`PPFNet: Global Context Aware Local Features for Robust 3D Point Matching

`_

    | :authors:`Haowen Deng, Tolga Birdal, Slobodan Ilic`

    | :venue:`CVPR 2018`



`Iterative Visual Reasoning Beyond Convolutions

`_

    | :authors:`Xinlei Chen, Li-Jia Li, Li Fei-Fei, Abhinav Gupta`

    | :venue:`CVPR 2018`



`Surface Networks

`_

    | :authors:`Ilya Kostrikov, Zhongshi Jiang, Daniele Panozzo, Denis Zorin, Joan Bruna`

    | :venue:`CVPR 2018`



`FeaStNet: Feature-Steered Graph Convolutions for 3D Shape Analysis

`_

    | :authors:`Nitika Verma, Edmond Boyer, Jakob Verbeek`

    | :venue:`CVPR 2018`



`Learning to Act Properly: Predicting and Explaining Affordances From Images

`_

    | :authors:`Ching-Yao Chuang, Jiaman Li, Antonio Torralba, Sanja Fidler`

    | :venue:`CVPR 2018`



`Mining Point Cloud Local Structures by Kernel Correlation and Graph Pooling

`_

    | :authors:`Yiru Shen, Chen Feng, Yaoqing Yang, Dong Tian`

    | :venue:`CVPR 2018`



`Deformable Shape Completion With Graph Convolutional Autoencoders

`_

    | :authors:`Or Litany, Alex Bronstein, Michael Bronstein, Ameesh Makadia`

    | :venue:`CVPR 2018`



`Pixel2Mesh: Generating 3D Mesh Models from Single RGB Images

`_

    | :authors:`Nanyang Wang, Yinda Zhang, Zhuwen Li, Yanwei Fu, Wei Liu, Yu-Gang Jiang`

    | :venue:`ECCV 2018`



`Learning Human-Object Interactions by Graph Parsing Neural Networks

`_

    | :authors:`Siyuan Qi, Wenguan Wang, Baoxiong Jia, Jianbing Shen, Song-Chun Zhu`

    | :venue:`ECCV 2018`



`Generating 3D Faces using Convolutional Mesh Autoencoders

`_

    | :authors:`Anurag Ranjan, Timo Bolkart, Soubhik Sanyal, Michael J. Black`

    | :venue:`ECCV 2018`



`Learning SO(3) Equivariant Representations with Spherical CNNs

`_

    | :authors:`Carlos Esteves, Christine Allen-Blanchette, Ameesh Makadia, Kostas Daniilidis`

    | :venue:`ECCV 2018`



`Neural Graph Matching Networks for Fewshot 3D Action Recognition

`_

    | :authors:`Michelle Guo, Edward Chou, De-An Huang, Shuran Song, Serena Yeung, Li Fei-Fei`

    | :venue:`ECCV 2018`



`Multi-Kernel Diffusion CNNs for Graph-Based Learning on Point Clouds

`_

    | :authors:`Lasse Hansen, Jasper Diesel, Mattias P. Heinrich`

    | :venue:`ECCV 2018`



`Hierarchical Video Frame Sequence Representation with Deep Convolutional Graph Network

`_

    | :authors:`Feng Mao, Xiang Wu, Hui Xue, Rong Zhang`

    | :venue:`ECCV 2018`



`Graph R-CNN for Scene Graph Generation

`_

    | :authors:`Jianwei Yang, Jiasen Lu, Stefan Lee, Dhruv Batra, Devi Parikh`

    | :venue:`ECCV 2018`



`Exploring Visual Relationship for Image Captioning

`_

    | :authors:`Ting Yao, Yingwei Pan, Yehao Li, Tao Mei`

    | :venue:`ECCV 2018`



`Beyond Grids: Learning Graph Representations for Visual Recognition

`_

    | :authors:`Yin Li, Abhinav Gupta`

    | :venue:`NeurIPS 2018`



`Learning Conditioned Graph Structures for Interpretable Visual Question Answering

`_

    | :authors:`Will Norcliffe-Brown, Efstathios Vafeias, Sarah Parisot`

    | :venue:`NeurIPS 2018`



`LinkNet: Relational Embedding for Scene Graph

`_

    | :authors:`Sanghyun Woo, Dahun Kim, Donghyeon Cho, In So Kweon`

    | :venue:`NeurIPS 2018`



`Flexible Neural Representation for Physics Prediction

`_

    | :authors:`Damian Mrowca, Chengxu Zhuang, Elias Wang, Nick Haber, Li Fei-Fei, Joshua B. Tenenbaum, Daniel L. K. Yamins`

    | :venue:`NeurIPS 2018`



`Learning Localized Generative Models for 3D Point Clouds via Graph Convolution

`_

    | :authors:`Diego Valsesia, Giulia Fracastoro, Enrico Magli`

    | :venue:`ICLR 2019`



`Graph-Based Global Reasoning Networks

`_

    | :authors:`Yunpeng Chen, Marcus Rohrbach, Zhicheng Yan, Shuicheng Yan, Jiashi Feng, Yannis Kalantidis`

    | :venue:`CVPR 2019`



`Deep Graph Laplacian Regularization for Robust Denoising of Real Images

`_

    | :authors:`Jin Zeng, Jiahao Pang, Wenxiu Sun, Gene Cheung`

    | :venue:`CVPR 2019`



`Learning Context Graph for Person Search

`_

    | :authors:`Yichao Yan, Qiang Zhang, Bingbing Ni, Wendong Zhang, Minghao Xu, Xiaokang Yang`

    | :venue:`CVPR 2019`



`Graphonomy: Universal Human Parsing via Graph Transfer Learning

`_

    | :authors:`Ke Gong, Yiming Gao, Xiaodan Liang, Xiaohui Shen, Meng Wang, Liang Lin`

    | :venue:`CVPR 2019`



`Masked Graph Attention Network for Person Re-Identification

`_

for_Person_Re-Identification_CVPRW_2019_paper.html>`_

    | :authors:`Liqiang Bao, Bingpeng Ma, Hong Chang, Xilin Chen`

    | :venue:`CVPR 2019`



`Learning to Cluster Faces on an Affinity Graph

`_

    | :authors:`Lei Yang, Xiaohang Zhan, Dapeng Chen, Junjie Yan, Chen Change Loy, Dahua Lin`

    | :venue:`CVPR 2019`



`Actional-Structural Graph Convolutional Networks for Skeleton-Based Action Recognition

`_

    | :authors:`Maosen Li, Siheng Chen, Xu Chen, Ya Zhang, Yanfeng Wang, Qi Tian`

    | :venue:`CVPR 2019`



`Adaptively Connected Neural Networks

`_

    | :authors:`Guangrun Wang, Keze Wang, Liang Lin`

    | :venue:`CVPR 2019`



`Reasoning Visual Dialogs with Structural and Partial Observations

`_

    | :authors:`Zilong Zheng, Wenguan Wang, Siyuan Qi, Song-Chun Zhu`

    | :venue:`CVPR 2019`



`MeshCNN: A Network with an Edge

`_

    | :authors:`Rana Hanocka, Amir Hertz, Noa Fish, Raja Giryes, Shachar Fleishman, Daniel Cohen-Or`

    | :venue:`SIGGRAPH 2019`

    | :keywords:`https://ranahanocka.github.io/MeshCNN/`



`Symmetric Graph Convolutional Autoencoder for Unsupervised Graph Representation Learning

`_

    | :authors:`Jiwoong Park, Minsik Lee, Hyung Jin Chang, Kyuewang Lee, Jin Young Choi`

    | :venue:`ICCV 2019`



`Pixel2Mesh++: Multi-View 3D Mesh Generation via Deformation

`_

    | :authors:`Chao Wen, Yinda Zhang, Zhuwen Li, Yanwei Fu`

    | :venue:`ICCV 2019`



`Learning Trajectory Dependencies for Human Motion Prediction

`_

    | :authors:`Wei Mao, Miaomiao Liu, Mathieu Salzmann, Hongdong Li`

    | :venue:`ICCV 2019`



`Graph-Based Object Classification for Neuromorphic Vision Sensing

`_

    | :authors:`Yin Bi, Aaron Chadha, Alhabib Abbas, Eirina Bourtsoulatze, Yiannis Andreopoulos`

    | :venue:`ICCV 2019`



`Fashion Retrieval via Graph Reasoning Networks on a Similarity Pyramid

`_

    | :authors:`Zhanghui Kuang, Yiming Gao, Guanbin Li, Ping Luo, Yimin Chen, Liang Lin, Wayne Zhang`

    | :venue:`ICCV 2019`



`Understanding Human Gaze Communication by Spatio-Temporal Graph Reasoning

`_

    | :authors:`Lifeng Fan, Wenguan Wang, Siyuan Huang, Xinyu Tang, Song-Chun Zhu`

    | :venue:`ICCV 2019`



`Visual Semantic Reasoning for Image-Text Matching

`_

    | :authors:`Kunpeng Li, Yulun Zhang, Kai Li, Yuanyuan Li, Yun Fu`

    | :venue:`ICCV 2019`



`Graph Convolutional Networks for Temporal Action Localization

`_

    | :authors:`Runhao Zeng, Wenbing Huang, Mingkui Tan, Yu Rong, Peilin Zhao, Junzhou Huang, Chuang Gan`

    | :venue:`ICCV 2019`



`Semantically-Regularized Logic Graph Embeddings

`_

    | :authors:`Yaqi Xie, Ziwei Xu, Kuldeep Meel, Mohan S Kankanhalli, Harold Soh`

    | :venue:`NeurIPS 2019`



Recommender Systems

-------------------



`Graph Convolutional Neural Networks for Web-Scale Recommender Systems

`_

    | :authors:`Rex Ying, Ruining He, Kaifeng Chen, Pong Eksombatchai, William L. Hamilton, Jure Leskovec`

    | :venue:`KDD 2018`

    | :keywords:`PinSage`



`SocialGCN: An Efficient Graph Convolutional Network based Model for Social Recommendation

`_

    | :authors:`Le Wu, Peijie Sun, Richang Hong, Yanjie Fu, Xiting Wang, Meng Wang`

    | :venue:`AAAI 2018`

    | :keywords:`GCN, Social recommendation`



`Session-based Social Recommendation via Dynamic Graph Attention Networks

`_

    | :authors:`Weiping Song, Zhiping Xiao, Yifan Wang, Laurent Charlin, Ming Zhang, Jian Tang`

    | :venue:`WSDM 2019`

    | :keywords:`Social recommendation, session-based, GAT`



`Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in

Recommender Systems

`_

    | :authors:`Qitian Wu, Hengrui Zhang, Xiaofeng Gao, Peng He, Paul Weng, Han Gao, Guihai Chen`

    | :venue:`WWW 2019`

    | :keywords:`Social recommendation, GAT`



`Graph Neural Networks for Social Recommendation

`_

    | :authors:`Wenqi Fan, Yao Ma, Qing Li, Yuan He, Eric Zhao, Jiliang Tang, Dawei Yin`

    | :venue:`WWW 2019`

    | :keywords:`Social recommendation, GNN`



`Session-based Recommendation with Graph Neural Networks

`_

    | :authors:`Shu Wu, Yuyuan Tang, Yanqiao Zhu, Liang Wang, Xing Xie, Tieniu Tan`

    | :venue:`AAAI 2019`

    | :keywords:`Session-based recommendation, GNN`



`A Neural Influence Diffusion Model for Social Recommendation

`_

    | :authors:`Le Wu, Peijie Sun, Yanjie Fu, Richang Hong, Xiting Wang, Meng Wang`

    | :venue:`SIGIR 2019`

    | :keywords:`Social Recommendation, diffusion`



`Neural Graph Collaborative Filtering

`_

    | :authors:`Xiang Wang, Xiangnan He, Meng Wang, Fuli Feng, Tat-Seng Chua`

    | :venue:`SIGIR 2019`

    | :keywords:`Collaborative Filtering, GNN`



`Binarized Collaborative Filtering with Distilling Graph Convolutional Networks

`_

    | :authors:`Haoyu Wang, Defu Lian, Yong Ge`

    | :venue:`IJCAI 2019`



`IntentGC: A Scalable Graph Convolution Framework Fusing Heterogeneous Information for Recommendation

`_

    | :authors:`Jun Zhao, Zhou Zhou, Ziyu Guan, Wei Zhao, Wei Ning, Guang Qiu, Xiaofei He`

    | :venue:`KDD 2019`



`An End-to-End Neighborhood-based Interaction Model for Knowledge-enhanced Recommendation

`_

    | :authors:`Yanru Qu, Ting Bai, Weinan Zhang, Jianyun Nie, Jian Tang`

    | :venue:`KDD 2019 Workshop`



Link Prediction

---------------



`Link Prediction Based on Graph Neural Networks

`_

    | :authors:`Muhan Zhang, Yixin Chen`

    | :venue:`NeurIPS 2018`



`Link Prediction via Subgraph Embedding-Based Convex Matrix Completion

`_

    | :authors:`Zhu Cao, Linlin Wang, Gerard de Melo`

    | :venue:`AAAI 2018`



`Graph Convolutional Matrix Completion

`_

    | :authors:`Rianne van den Berg, Thomas N. Kipf, Max Welling`

    | :venue:`KDD 2018 Workshop`



`Semi-Implicit Graph Variational Auto-Encoders

`_

    | :authors:`Arman Hasanzadeh, Ehsan Hajiramezanali, Nick Duffield , Krishna Narayanan, Mingyuan Zhou, Xiaoning Qian`

    | :venue:`NeurIPS 2019`



Influence Prediction

--------------------



`DeepInf: Social Influence Prediction with Deep Learning

`_

    | :authors:`Jiezhong Qiu, Jian Tang, Hao Ma, Yuxiao Dong, Kuansan Wang, Jie Tang`

    | :venue:`KDD 2018`



`Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks

`_

    | :authors:`Namyong Park, Andrey Kan, Xin Luna Dong, Tong Zhao, Christos Faloutsos`

    | :venue:`KDD 2019`



Neural Architecture Search

--------------------------



`Graph HyperNetworks for Neural Architecture Search

`_

    | :authors:`Chris Zhang, Mengye Ren, Raquel Urtasun`

    | :venue:`ICLR 2019`



`D-VAE: A Variational Autoencoder for Directed Acyclic Graphs

`_

    | :authors:`Muhan Zhang, Shali Jiang, Zhicheng Cui, Roman Garnett, Yixin Chen`

    | :venue:`NeurIPS 2019`



Reinforcement Learning

----------------------



`Action Schema Networks: Generalised Policies with Deep Learning

`_

    | :authors:`Sam Toyer, Felipe Trevizan, Sylvie Thiebaux, Lexing Xie`

    | :venue:`AAAI 2018`



`NerveNet: Learning Structured Policy with Graph Neural Networks

`_

    | :authors:`Tingwu Wang, Renjie Liao, Jimmy Ba, Sanja Fidler`

    | :venue:`ICLR 2018`



`Graph Networks as Learnable Physics Engines for Inference and Control

`_

    | :authors:`Alvaro Sanchez-Gonzalez, Nicolas Heess, Jost Tobias Springenberg, Josh Merel, Martin Riedmiller`

    | :venue:`ICML 2018`



`Learning Policy Representations in Multiagent Systems

`_

    | :authors:`Aditya Grover, Maruan Al-Shedivat, Jayesh K. Gupta, Yura Burda, Harrison Edwards`

    | :venue:`ICML 2018`



`Relational recurrent neural networks

`_

    | :authors:`Adam Santoro,  Ryan Faulkner, David Raposo, Jack Rae, Mike Chrzanowski,Théophane Weber, Daan Wierstra, Oriol Vinyals, Razvan Pascanu, Timothy Lillicrap`

    | :venue:`NeurIPS 2018`



`Transfer of Deep Reactive Policies for MDP Planning

`_

    | :authors:`Aniket Bajpai, Sankalp Garg, Mausam`

    | :venue:`NeurIPS 2018`



`Neural Graph Evolution: Towards Efficient Automatic Robot Design

`_

    | :authors:`Tingwu Wang, Yuhao Zhou, Sanja Fidler, Jimmy Ba`

    | :venue:`ICLR 2019`



`No Press Diplomacy: Modeling Multi-Agent Gameplay

`_

    | :authors:`Philip Paquette, Yuchen Lu, Steven Bocco, Max O. Smith, Satya Ortiz-Gagne, Jonathan K. Kummerfeld, Satinder Singh, Joelle Pineau, Aaron Courville`

    | :venue:`NeurIPS 2019`



Combinatorial Optimization

--------------------------



`Learning Combinatorial Optimization Algorithms over Graphs

`_

    | :authors:`Hanjun Dai, Elias B. Khalil, Yuyu Zhang, Bistra Dilkina, Le Song`

    | :venue:`NeurIPS 2017`



`Combinatorial Optimization with Graph Convolutional Networks and Guided Tree Search

`_

    | :authors:`Zhuwen Li, Qifeng Chen, Vladlen Koltun`

    | :venue:`NeurIPS 2018`



`Reinforcement Learning for Solving the Vehicle Routing Problem

`_

    | :authors:`Mohammadreza Nazari, Afshin Oroojlooy, Lawrence V. Snyder, Martin Takáč`

    | :venue:`NeurIPS 2018`

    

`Attention, Learn to Solve Routing Problems!

`_

    | :authors:`Wouter Kool, Herke van Hoof, Max Welling`

    | :venue:`ICLR 2019`

    

`Learning a SAT Solver from Single-Bit Supervision