This is a paper list about deep learning for graphs.
Laurens, van, der, Maaten, Geoffrey, HintonJMLR 2008
A Three-way Model for Collective Learning on Multi-relational Data.
Maximilian, Nickel, Volker, Tresp, Hans-Peter, KriegelICML 2011
Visualizing Non-metric Similarities in Multiple Maps
Laurens, van, der, Maaten, Geoffrey, HintonML 2012
Translating Embeddings for Modeling Multi-relational Data
Antoine, Bordes, Nicolas, Usunier, Alberto, Garcia-Duran, Jason, Weston, Oksana, YakhnenkoNIPS 2013
Learning Latent Representations of Nodes for Classifying in Heterogeneous Social Networks
Yann, Jacob, Ludovic, Denoyer, Patrick, GallinariWSDM 2014
Knowledge Graph Embedding by Translating on Hyperplanes
Zhen, Wang, Jianwen, Zhang, Jianlin, Feng, Zheng, ChenAAAI 2014
Deepwalk: Online Learning of Social Representations
Bryan, Perozzi, Rami, Al-Rfou, Steven, SkienaKDD 2014Node, classification, Random, walk, Skip-gram
Reducing the Rank of Relational Factorization Models by Including Observable Patterns
Maximilian, Nickel, Xueyan, Jiang, Volker, TrespNIPS 2014
Network Representation Learning with Rich Text Information
Cheng, Yang, Zhiyuan, Liu, Deli, Zhao, Maosong, Sun, Edward, ChangAAAI 2015
Learning Entity and Relation Embeddings for Knowledge Graph Completion
Yankai, Lin, Zhiyuan, Liu, Maosong, Sun, Yang, Liu, Xuan, ZhuAAAI 2015
Knowledge Graph Embedding via Dynamic Mapping Matrix
Guoliang, Ji, Shizhu, He, Liheng, Xu, Kang, Liu, Jun, ZhaACL 2015
Grarep: Learning Graph Representations with Global Structural Information
Shaosheng, Cao, Wei, Lu, Qiongkai, XuCIKM 2015High-order, SVD
Modeling Relation Paths for Representation Learning of Knowledge Bases
Yankai, Lin, Zhiyuan, Liu, Huanbo, Luan, Maosong, Sun, Siwei, Rao, Song, LiuEMNLP 2015
Embedding Entities and Relations for Learning and Inference in Knowledge Bases
Bishan, Yang, Wen-tau, Yih, Xiaodong, He, Jianfeng, Gao, Li, DengICLR 2015
A Review of Relational Machine Learning for Knowledge Graph
Maximilian, Nickel, Kevin, Murphy, Volker, Tresp, Evgeniy, GabrilovichIEEE 2015
Pte: Predictive Text Embedding through Large-scale Heterogeneous Text Networks
Jian, Tang, Meng, Qu, Qiaozhu, MeiKDD 2015Text, Embedding, Heterogeneous, Text, Graphs
Heterogeneous Network Embedding via Deep Architectures
Shiyu, Chang, Wei, Han, Jiliang, Tang, Guo-Jun, Qi, Charu, C., Aggarwal, Thomas, S., HuangKDD 2015
Line: Large-scale Information Network Embedding
Jian, Tang, Meng, Qu, Mingzhe, Wang, Ming, Zhang, Jun, Yan, Qiaozhu, MeiWWW 2015First-order, Second-order, Node, classification
Variational Graph Auto-encoders
Thomas, N., Kipf, Max, WellingarXiv 2016
Meta-path Guided Embedding for Similarity Search in Large-scale Heterogeneous Information Networks
Jingbo, Shang, Meng, Qu, Jialu, Liu, Lance, M., Kaplan, Jiawei, Han, Jian, PengarXiv 2016
Max-margin Deepwalk: Discriminative Learning of Network Representation
Cunchao, Tu, Weicheng, Zhang, Zhiyuan, Liu, Maosong, SunIJCAI 2016
Holographic Embeddings of Knowledge Graphs
Maximilian, Nickel, Lorenzo, Rosasco, Tomaso, PoggioAAAI 2016
Complex Embeddings for Simple Link Prediction
Théo, Trouillon, Johannes, Welbl, Sebastian, Riedel, Éric, Gaussier, Guillaume, BouchardICML 2016
Revisiting Semi-supervised Learning with Graph Embeddings
Zhilin, Yang, William, W., Cohen, Ruslan, SalakhutdinovICML 2016
Visualizing Large-scale and High-dimensional Data
Jian, Tang, Jingzhou, Liu, Ming, Zhang, Qiaozhu, MeiWWW 2016
Node2vec: Scalable Feature Learning for Networks
Aditya, Grover, Jure, LeskovecKDD 2016Breadth-first, Search, Depth-first, Search, Node, Classification, Link, Prediction
Scalable Graph Embedding for Asymmetric Proximity
Chang, Zhou, Yuqiong, Liu, Xiaofei, Liu, Zhongyi, Liu, Jun, GaoAAAI 2017
Cane: Context-aware Network Embedding for Relation Modeling
Cunchao, Tu, Han, Liu, Zhiyuan, Liu, Maosong, SunACL 2017
Hin2vec: Explore Meta-paths in Heterogeneous Information Networks for Representation Learning
Tao-yang, Fu, Wang-Chien, Lee, Zhen, LeiCIKM 2017
An Attention-based Collaboration Framework for Multi-view Network Representation Learning
Meng, Qu, Jian, Tang, Jingbo, Shang, Xiang, Ren, Ming, Zhang, Jiawei, HanCIKM 2017
Multi-view Clustering with Graph Embedding for Connectome Analysis
Guixiang, Ma, Lifang, He, Chun-Ta, Lu, Weixiang, Shao, Philip, S., Yu, Alex, D., Leow, Ann, B., RaginCIKM 2017
Attributed Signed Network Embedding
Suhang, Wang, Charu, Aggarwal, Jiliang, Tang, Huan, LiuCIKM 2017
Attributed Network Embedding for Learning in a Dynamic Environment
Jundong, Li, Harsh, Dani, Xia, Hu, Jiliang, Tang, Yi, Chang, Huan, LiuCIKM 2017
Graph-based Neural Multi-document Summarization
Michihiro, Yasunaga, Rui, Zhang, Kshitijh, Meelu, Ayush, Pareek, Krishnan, Srinivasan, Dragomir, RadevCoNLL 2017
Encoding Sentences with Graph Convolutional Networks for Semantic Role Labeling
Diego, Marcheggiani, Ivan, TitovEMNLP 2017
Graph Convolutional Encoders for Syntax-aware Neural Machine Translation
Joost, Bastings, Ivan, Titov, Wilker, Aziz, Diego, Marcheggiani, Khalil, Sima’anEMNLP 2017
3d Graph Neural Networks for Rgbd Semantic Segmentation
Xiaojuan, Qi, Renjie, Liao, Jiaya, Jia, Sanja, Fidler, Raquel, UrtasunICCV 2017
Situation Recognition With Graph Neural Networks
Ruiyu, Li, Makarand, Tapaswi, Renjie, Liao, Jiaya, Jia, Raquel, Urtasun, Sanja, FidlerICCV 2017
Graph-based Classification of Omnidirectional Images
Renata, Khasanova, Pascal, FrossardICCV 2017
Dyngem: Deep Embedding Method for Dynamic Graphs
Palash, Goyal, Nitin, Kamra, Xinran, He, Yan, LiuICLR 2017 Workshop
Semi-supervised Classification with Graph Convolutional Networks
Thomas, N., Kipf, Max, WellingICLR 2017
Know-evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs
Rakshit, Trivedi, Hanjun, Dai, Yichen, Wang, Le, SongICML 2017
Neural Message Passing for Quantum Chemistry
Justin, Gilmer, Samuel, S., Schoenholz, Patrick, F., Riley, Oriol, Vinyals, George, E., DahlICML 2017
Fast Network Embedding Enhancement via High Order Proximity Approximation
Cheng, Yang, Maosong, Sun, Zhiyuan, Liu, Cunchao, TuIJCAI 2017
Hoang, Nguyen, Tsuyoshi, MurataIJCAI 2017
Struc2vec: Learning Node Representations from Structural Identity
Leonardo, F., R., Ribeiro, Pedro, H., P., Savarese, Daniel, R., FigueiredoKDD 2017Structural, Identity
Metapath2vec: Scalable Representation Learning for Heterogeneous Networks
Yuxiao, Dong, Nitesh, V., Chawla, Ananthram, SwamiKDD 2017
Poincaré Embeddings for Learning Hierarchical Representations
Maximilian, Nickel, Douwe, KielaNIPS 2017
Learning Graph Representations with Embedding Propagation
Alberto, Garcia-Duran, Mathias, NiepertNIPS 2017
Inductive Representation Learning on Large Graphs
William, L., Hamilton, Rex, Ying, Jure, LeskovecNIPS 2017
Learning Combinatorial Optimization Algorithms over Graphs
Hanjun, Dai, Elias, B., Khalil, Yuyu, Zhang, Bistra, Dilkina, Le, SongNeurIPS 2017
Protein Interface Prediction Using Graph Convolutional Networks
Alex, Fout, Jonathon, Byrd, Basir, Shariat, Asa, Ben-HurNeurIPS 2017
Premise Selection for Theorem Proving by Deep Graph Embedding
Mingzhe, Wang, Yihe, Tang, Jian, Wang, Jia, DengNeurIPS 2017
Modeling Relational Data with Graph Convolutional Networks
Michael, Schlichtkrull, Thomas, N., Kipf, Peter, Bloem, Rianne, Van, Den, Berg, Ivan, Titov, Max, WellingarXiv 2017
Fast Linear Model for Knowledge Graph Embeddings
Armand, Joulin, Edouard, Grave, Piotr, Bojanowski, Maximilian, Nickel, Tomas, MikolovarXiv 2017
Quanyu, Dai, Qiang, Li, Jian, Tang, Dan, WangAAAI 2018
Graphgan: Graph Representation Learning with Generative Adversarial Nets
Hongwei, Wang, Jia, Wang, Jialin, Wang, Miao, Zhao, Weinan, Zhang, Fuzheng, Zhang, Xing, Xie, Minyi, GuoAAAI 2018
Starspace: Embed All The Things
Ledell, Wu, Adam, Fisch, Sumit, Chopra, Keith, Adams, Antoine, Bordes, Jason, WestonAAAI 2018
Xiaoyan, Cai, Junwei, Han, Libin, YangAAAI 2018
Dynamic Network Embedding by Modeling Triadic Closure Process
Lekui, Zhou, Yang, Yang, Xiang, Ren, Fei, Wu, Yueting, ZhuangAAAI 2018
Depthlgp: Learning Embeddings of Out-of-sample Nodes in Dynamic Networks
Jianxin, Ma, Peng, Cui, Wenwu, ZhuAAAI 2018
Timers: Error-bounded Svd Restart on Dynamic Networks
Ziwei, Zhang, Peng, Cui, Jian, Pei, Xiao, Wang, Wenwu, ZhuAAAI 2018
Convolutional 2d Knowledge Graph Embeddings
Tim, Dettmers, Pasquale, Minervini, Pontus, Stenetorp, Sebastian, RiedelAAAI 2018
Knowledge Graph Embedding With Iterative Guidance From Soft Rules
Shu, Guo, Quan, Wang, Lihong, Wang, Bin, Wang, Li, GuoAAAI 2018
Spatial Temporal Graph Convolutional Networks for Skeleton-based Action Recognition
Sijie, Yan, Yuanjun, Xiong, Dahua, LinAAAI 2018
Socialgcn: An Efficient Graph Convolutional Network Based Model for Social Recommendation
Le, Wu, Peijie, Sun, Richang, Hong, Yanjie, Fu, Xiting, Wang, Meng, WangAAAI 2018GCN, Social, recommendation
Link Prediction via Subgraph Embedding-based Convex Matrix Completion
Zhu, Cao, Linlin, Wang, Gerard, de, MeloAAAI 2018
Action Schema Networks: Generalised Policies with Deep Learning
Sam, Toyer, Felipe, Trevizan, Sylvie, Thiebaux, Lexing, XieAAAI 2018
Improving Knowledge Graph Embedding Using Simple Constraints
Boyang, Ding, Quan, Wang, Bin, Wang, Li, GuoACL 2018
A Graph-to-sequence Model for Amr-to-text Generation
Linfeng, Song, Yue, Zhang, Zhiguo, Wang, Daniel, GildeaACL 2018
Graph-to-sequence Learning Using Gated Graph Neural Networks
Daniel, Beck, Gholamreza, Haffari, Trevor, CohnACL 2018
Modeling Polypharmacy Side Effects with Graph Convolutional Networks
Marinka, Zitnik, Monica, Agrawal, Jure, LeskovecBioinformatics 2018
Neodti: Neural Integration of Neighbor Information from a Heterogeneous Network for Discovering New
Fangping, Wan, Lixiang, Hong, An, Xiao, Tao, Jiang, Jianyang, ZengBioinformatics 2018
Regal: Representation Learning-based Graph Alignment
Mark, Heimann, Haoming, Shen, Tara, Safavi, Danai, KoutraCIKM 2018
Modeling Semantics with Gated Graph Neural Networks for Knowledge Base Question Answering
Daniil, Sorokin, Iryna, GurevychCOLING 2018
Image Generation from Scene Graphs
Justin, Johnson, Agrim, Gupta, Li, Fei-FeiCVPR 2018
Foldingnet: Point Cloud Auto-encoder via Deep Grid Deformation
Yaoqing, Yang, Chen, Feng, Yiru, Shen, Dong, TianCVPR 2018
Ppfnet: Global Context Aware Local Features for Robust 3d Point Matching
Haowen, Deng, Tolga, Birdal, Slobodan, IlicCVPR 2018
Iterative Visual Reasoning Beyond Convolutions
Xinlei, Chen, Li-Jia, Li, Li, Fei-Fei, Abhinav, GuptaCVPR 2018
Ilya, Kostrikov, Zhongshi, Jiang, Daniele, Panozzo, Denis, Zorin, Joan, BrunaCVPR 2018
Feastnet: Feature-steered Graph Convolutions for 3d Shape Analysis
Nitika, Verma, Edmond, Boyer, Jakob, VerbeekCVPR 2018
Learning to Act Properly: Predicting and Explaining Affordances From Images
Ching-Yao, Chuang, Jiaman, Li, Antonio, Torralba, Sanja, FidlerCVPR 2018
Mining Point Cloud Local Structures by Kernel Correlation and Graph Pooling
Yiru, Shen, Chen, Feng, Yaoqing, Yang, Dong, TianCVPR 2018
Deformable Shape Completion With Graph Convolutional Autoencoders
Or, Litany, Alex, Bronstein, Michael, Bronstein, Ameesh, MakadiaCVPR 2018
Pixel2mesh: Generating 3d Mesh Models from Single Rgb Images
Nanyang, Wang, Yinda, Zhang, Zhuwen, Li, Yanwei, Fu, Wei, Liu, Yu-Gang, JiangECCV 2018
Learning Human-object Interactions by Graph Parsing Neural Networks
Siyuan, Qi, Wenguan, Wang, Baoxiong, Jia, Jianbing, Shen, Song-Chun, ZhuECCV 2018
Generating 3d Faces Using Convolutional Mesh Autoencoders
Anurag, Ranjan, Timo, Bolkart, Soubhik, Sanyal, Michael, J., BlackECCV 2018
Learning So(3) Equivariant Representations with Spherical Cnns
Carlos, Esteves, Christine, Allen-Blanchette, Ameesh, Makadia, Kostas, DaniilidisECCV 2018
Neural Graph Matching Networks for Fewshot 3d Action Recognition
Michelle, Guo, Edward, Chou, De-An, Huang, Shuran, Song, Serena, Yeung, Li, Fei-FeiECCV 2018
Multi-kernel Diffusion Cnns for Graph-based Learning on Point Clouds
Lasse, Hansen, Jasper, Diesel, Mattias, P., HeinrichECCV 2018
Hierarchical Video Frame Sequence Representation with Deep Convolutional Graph Network
Feng, Mao, Xiang, Wu, Hui, Xue, Rong, ZhangECCV 2018
Graph R-cnn for Scene Graph Generation
Jianwei, Yang, Jiasen, Lu, Stefan, Lee, Dhruv, Batra, Devi, ParikhECCV 2018
Exploring Visual Relationship for Image Captioning
Ting, Yao, Yingwei, Pan, Yehao, Li, Tao, MeiECCV 2018
Linguistically-informed Self-attention for Semantic Role Labeling
Emma, Strubell, Patrick, Verga, Daniel, Andor, David, Weiss, Andrew, McCallumEMNLP 2018
Graph Convolution over Pruned Dependency Trees Improves Relation Extraction
Yuhao, Zhang, Peng, Qi, Christopher, D., ManningEMNLP 2018
Cross-lingual Knowledge Graph Alignment via Graph Convolutional Networks
Zhichun, Wang, Qingsong, Lv, Xiaohan, Lan, Yu, ZhangEMNLP 2018
Meta-graph Based Hin Spectral Embedding: Methods, Analyses, and Insights
Carl, Yang, Yichen, Feng, Pan, Li, Yu, Shi, Jiawei, HanICDM 2018
Petar, Veličković, Guillem, Cucurull, Arantxa, Casanova, Adriana, Romero, Pietro, Liò, Yoshua, BengioICLR 2018
Fastgcn: Fast Learning with Graph Convolutional Networks via Importance Sampling
Jie, Chen, Tengfei, Ma, Cao, XiaoICLR 2018
Qanet: Combining Local Convolution with Global Self-attention for Reading Comprehension
Adams, Wei, Yu, David, Dohan, Minh-Thang, Luong, Rui, Zhao, Kai, Chen, Mohammad, Norouzi, Quoc, V., LeICLR 2018
A Structured Self-attentive Sentence Embedding
Zhouhan, Lin, Minwei, Feng, Cicero, Nogueira, dos, Santos, Mo, Yu, Bing, Xiang, Bowen, Zhou, Yoshua, BengioICLR 2018
Nervenet: Learning Structured Policy with Graph Neural Networks
Tingwu, Wang, Renjie, Liao, Jimmy, Ba, Sanja, FidlerICLR 2018
Few-shot Learning with Graph Neural Networks
Victor, Garcia, Joan, BrunaICLR 2018
Representation Learning on Graphs with Jumping Knowledge Networks
Keyulu, Xu, Chengtao, Li, Yonglong, Tian, Tomohiro, Sonobe, Ken-ichi, Kawarabayashi, Stefanie, JegelkaICML 2018
Stochastic Training of Graph Convolutional Networks with Variance Reduction
Jianfei, Chen, Jun, Zhu, Le, SongICML 2018
Graph Networks As Learnable Physics Engines for Inference and Control
Alvaro, Sanchez-Gonzalez, Nicolas, Heess, Jost, Tobias, Springenberg, Josh, Merel, Martin, RiedmillerICML 2018
Learning Policy Representations in Multiagent Systems
Aditya, Grover, Maruan, Al-Shedivat, Jayesh, K., Gupta, Yura, Burda, Harrison, EdwardsICML 2018
Adversarial Attack on Graph Structured Data
Hanjun, Dai, Hui, Li, Tian, Tian, Xin, Huang, Lin, Wang, Jun, Zhu, Le, SongICML 2018
Learning Steady-states of Iterative Algorithms over Graphs
Hanjun, Dai, Zornitsa, Kozareva, Bo, Dai, Alex, Smola, Le, SongICML 2018
Neural Relational Inference for Interacting Systems
Thomas, Kipf, Ethan, Fetaya, Kuan-Chieh, Wang, Max, Welling, Richard, ZemelICML 2018
Graphrnn: Generating Realistic Graphs with Deep Auto-regressive Models
Jiaxuan, You, Rex, Ying, Xiang, Ren, William, L., Hamilton, Jure, LeskovecICML 2018
Netgan: Generating Graphs via Random Walks
Aleksandar, Bojchevski, Oleksandr, Shchur, Daniel, Zügner, Stephan, GünnemannICML 2018
Learning Deep Generative Models of Graphs
Yujia, Li, Oriol, Vinyals, Chris, Dyer, Razvan, Pascanu, Peter, BattagliaICML 2018
Junction Tree Variational Autoencoder for Molecular Graph Generation
Wengong, Jin, Regina, Barzilay, Tommi, JaakkolaICML 2018
Anrl: Attributed Network Representation Learning via Deep Neural Networks
Zhen, Zhang, Hongxia, Yang, Jiajun, Bu, Sheng, Zhou, Pinggang, Yu, Jianwei, Zhang, Martin, Ester, Can, WangIJCAI 2018
Efficient Attributed Network Embedding via Recursive Randomized Hashing
Wei, Wu, Bin, Li, Ling, Chen, Chengqi, ZhangIJCAI 2018
Deep Attributed Network Embedding
Hongchang, Gao, Heng, HuangIJCAI 2018
Dynamic Network Embedding : An Extended Approach for Skip-gram Based Network Embedding
Lun, Du, Yun, Wang, Guojie, Song, Zhicong, Lu, Junshan, WangIJCAI 2018
Learning Structural Node Embeddings via Diffusion Wavelets
Claire, Donnat, Marinka, Zitnik, David, Hallac, Jure, LeskovecKDD 2018
Pme: Projected Metric Embedding on Heterogeneous Networks for Link Prediction
Hongxu, Chen, Hongzhi, Yin, Weiqing, Wang, Hao, Wang, Quoc, Viet, Hung, Nguyen, Xue, LiKDD 2018
Easing Embedding Learning by Comprehensive Transcription of Heterogeneous Information Networks
Yu, Shi, Qi, Zhu, Fang, Guo, Chao, Zhang, Jiawei, HanKDD 2018
Dynamic Embeddings for User Profiling in Twitter
Shangsong, Liang, Xiangliang, Zhang, Zhaochun, Ren, Evangelos, KanoulasKDD 2018
Large-scale Learnable Graph Convolutional Networks
Hongyang, Gao, Zhengyang, Wang, Shuiwang, JiKDD 2018
Graph Convolutional Neural Networks for Web-scale Recommender Systems
Rex, Ying, Ruining, He, Kaifeng, Chen, Pong, Eksombatchai, William, L., Hamilton, Jure, LeskovecKDD 2018P, i, n, S, a, g, e
Graph Convolutional Matrix Completion
Rianne, van, den, Berg, Thomas, N., Kipf, Max, WellingKDD 2018 Workshop
Deepinf: Social Influence Prediction with Deep Learning
Jiezhong, Qiu, Jian, Tang, Hao, Ma, Yuxiao, Dong, Kuansan, Wang, Jie, TangKDD 2018
Adversarial Attacks on Neural Networks for Graph Data
Daniel, Zügner, Amir, Akbarnejad, Stephan, GünnemannKDD 2018
Kbgan: Adversarial Learning for Knowledge Graph Embeddings
Liwei, Cai, William, Yang, WangNAACL 2018
A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network
Dai, Quoc, Nguyen, Tu, Dinh, Nguyen, Dat, Quoc, Nguyen, Dinh, PhungNAACL 2018
Exploiting Semantics in Neural Machine Translation with Graph Convolutional Networks
Diego, Marcheggiani, Joost, Bastings, Ivan, TitovNAACL 2018
Simple Embedding for Link Prediction in Knowledge Graphs
Seyed, Mehran, Kazemi, David, PooleNeurIPS 2018
Adaptive Sampling Towards Fast Graph Representation Learning
Wenbing, Huang, Tong, Zhang, Yu, Rong, Junzhou, HuangNeurIPS 2018
Hierarchical Graph Representation Learning with Differentiable Pooling
Rex, Ying, Jiaxuan, You, Christopher, Morris, Xiang, Ren, William, L., Hamilton, Jure, LeskovecNeurIPS 2018
Bayesian Semi-supervised Learning with Graph Gaussian Processes
Yin, Cheng, Ng, Nicolò, Colombo, Ricardo, SilvaNeurIPS 2018
Beyond Grids: Learning Graph Representations for Visual Recognition
Yin, Li, Abhinav, GuptaNeurIPS 2018
Learning Conditioned Graph Structures for Interpretable Visual Question Answering
Will, Norcliffe-Brown, Efstathios, Vafeias, Sarah, ParisotNeurIPS 2018
Linknet: Relational Embedding for Scene Graph
Sanghyun, Woo, Dahun, Kim, Donghyeon, Cho, In, So, KweonNeurIPS 2018
Flexible Neural Representation for Physics Prediction
Damian, Mrowca, Chengxu, Zhuang, Elias, Wang, Nick, Haber, Li, Fei-Fei, Joshua, B., Tenenbaum, Daniel, L., K., YaminsNeurIPS 2018
Link Prediction Based on Graph Neural Networks
Muhan, Zhang, Yixin, ChenNeurIPS 2018
Relational Recurrent Neural Networks
Adam, Santoro, Ryan, Faulkner, David, Raposo, Jack, Rae, Mike, Chrzanowski, Théophane, Weber, Daan, Wierstra, Oriol, Vinyals, Razvan, Pascanu, Timothy, LillicrapNeurIPS 2018
Transfer of Deep Reactive Policies for Mdp Planning
Aniket, Bajpai, Sankalp, Garg, MausamNeurIPS 2018
Combinatorial Optimization with Graph Convolutional Networks and Guided Tree Search
Zhuwen, Li, Qifeng, Chen, Vladlen, KoltunNeurIPS 2018
Reinforcement Learning for Solving the Vehicle Routing Problem
Mohammadreza, Nazari, Afshin, Oroojlooy, Lawrence, V., Snyder, Martin, TakáčNeurIPS 2018
Generative Modeling for Protein Structures
Namrata, Anand, Po-Ssu, HuangNeurIPS 2018
Constrained Generation of Semantically Valid Graphs via Regularizing Variational Autoencoders
Tengfei, Ma, Jie, Chen, Cao, XiaoNeurIPS 2018
Graph Convolutional Policy Network for Goal-directed Molecular Graph Generation
Jiaxuan, You, Bowen, Liu, Rex, Ying, Vijay, Pande, Jure, LeskovecNeurIPS 2018
Constrained Graph Variational Autoencoders for Molecule Design
Qi, Liu, Miltiadis, Allamanis, Marc, Brockschmidt, Alexander, L., GauntNeurIPS 2018
Bine: Bipartite Network Embedding
Ming, Gao, Leihui, Chen, Xiangnan, He, Aoying, ZhouSIGIR 2018
Network Embedding As Matrix Factorization: Unifying Deepwalk, Line, Pte, and Node2vec
Jiezhong, Qiu, Yuxiao, Dong, Hao, Ma, Jian, Li, Kuansan, Wang, Jie, TangWSDM 2018
Exploring Expert Cognition for Attributed Network Embedding
Xiao, Huang, Qingquan, Song, Jundong, Li, Xia, HuWSDM 2018
Shine: Signed Heterogeneous Information Network Embedding for Sentiment Link Prediction
Hongwei, Wang, Fuzheng, Zhang, Min, Hou, Xing, Xie, Minyi, Guo, Qi, LiuWSDM 2018
Multidimensional Network Embedding with Hierarchical Structures
Yao, Ma, Zhaochun, Ren, Ziheng, Jiang, Jiliang, Tang, Dawei, YinWSDM 2018
Curriculum Learning for Heterogeneous Star Network Embedding via Deep Reinforcement Learning
Meng, Qu, Jian, Tang, Jiawei, HanWSDM 2018
Verse: Versatile Graph Embeddings from Similarity Measures
Anton, Tsitsulin, Davide, Mottin, Panagiotis, Karras, Emmanuel, MüllerWWW 2018
Co-regularized Deep Multi-network Embedding
Jingchao, Ni, Shiyu, Chang, Xiao, Liu, Wei, Cheng, Haifeng, Chen, Dongkuan, Xu, Xiang, ZhangWWW 2018
Side: Representation Learning in Signed Directed Networks
Junghwan, Kim, Haekyu, Park, Ji-Eun, Lee, U, KangWWW 2018
Pitfalls of Graph Neural Network Evaluation
Oleksandr, Shchur, Maximilian, Mumme, Aleksandar, Bojchevski, Stephan, GünnemannarXiv 2018
Molgan: An Implicit Generative Model for Small Molecular Graphs
Nicola, De, Cao, Thomas, KipfarXiv 2018
A General View for Network Embedding As Matrix Factorization
Xin, Liu, Tsuyoshi, Murata, Kyoung-Sook, Kim, Chatchawan, Kotarasu, Chenyi, ZhuangWSDM 2019
Session-based Social Recommendation via Dynamic Graph Attention Networks
Weiping, Song, Zhiping, Xiao, Yifan, Wang, Laurent, Charlin, Ming, Zhang, Jian, TangWSDM 2019Social, recommendation, session-based, GAT
Petar, Veličković, William, Fedus, William, L., Hamilton, Pietro, Liò, Yoshua, Bengio, R, Devon, HjelmICLR 2019
Dyrep: Learning Representations over Dynamic Graphs
Rakshit, Trivedi, Mehrdad, Farajtabar, Prasenjeet, Biswal, Hongyuan, ZhaICLR 2019
Rotate: Knowledge Graph Embedding by Relational Rotation in Complex Space
Zhiqing, Sun, Zhi-Hong, Deng, Jian-Yun, Nie, Jian, TangICLR 2019
How Powerful Are Graph Neural Networks?
Keyulu, Xu, Weihua, Hu, Jure, Leskovec, Stefanie, JegelkaICLR 2019
Lanczosnet: Multi-scale Deep Graph Convolutional Networks
Renjie, Liao, Zhizhen, Zhao, Raquel, Urtasun, Richard, S., ZemelICLR 2019
Bingbing, Xu, Huawei, Shen, Qi, Cao, Yunqi, Qiu, Xueqi, ChengICLR 2019
Supervised Community Detection with Line Graph Neural Networks
Zhengdao, Chen, Xiang, Li, Joan, BrunaICLR 2019
Predict Then Propagate: Graph Neural Networks Meet Personalized Pagerank
Johannes, Klicpera, Aleksandar, Bojchevski, Stephan, GünnemannICLR 2019
Invariant and Equivariant Graph Networks
Haggai, Maron, Heli, Ben-Hamu, Nadav, Shamir, Yaron, LipmanICLR 2019
Zhang, Xinyi, Lihui, ChenICLR 2019
Differentiable Perturb-and-parse: Semi-supervised Parsing with a Structured Variational Autoencoder
Caio, Corro, Ivan, TitovICLR 2019
Structured Neural Summarization
Patrick, Fernandes, Miltiadis, Allamanis, Marc, BrockschmidICLR 2019
Learning Localized Generative Models for 3d Point Clouds via Graph Convolution
Diego, Valsesia, Giulia, Fracastoro, Enrico, MagliICLR 2019
Graph Hypernetworks for Neural Architecture Search
Chris, Zhang, Mengye, Ren, Raquel, UrtasunICLR 2019
Neural Graph Evolution: Towards Efficient Automatic Robot Design
Tingwu, Wang, Yuhao, Zhou, Sanja, Fidler, Jimmy, BaICLR 2019
Attention, Learn to Solve Routing Problems!
Wouter, Kool, Herke, van, Hoof, Max, WellingICLR 2019
Learning a Sat Solver from Single-bit Supervision
Daniel, Selsam, Matthew, Lamm, Benedikt, Bünz, Percy, Liang, Leonardo, de, Moura, David, L., DillICLR 2019
Adversarial Attacks on Graph Neural Networks via Meta Learning
Daniel, Zügner, Stephan, GünnemannICLR 2019
Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning
Yanbin, Liu, Juho, Lee, Minseop, Park, Saehoon, Kim, Eunho, Yang, Sung, Ju, Hwang, Yi, YangICLR 2019
Learning Multimodal Graph-to-graph Translation for Molecule Optimization
Wengong, Jin, Kevin, Yang, Regina, Barzilay, Tommi, JaakkolaICLR 2019
Generative Code Modeling with Graphs
Marc, Brockschmidt, Miltiadis, Allamanis, Alexander, L., Gaunt, Oleksandr, PolozovICLR 2019
Graphtsne: A Visualization Technique for Graph-structured Data
Yao, Yang, Leow, Thomas, Laurent, Xavier, BressonICLR 2019 Workshop
Netsmf: Large-scale Network Embedding As Sparse Matrix Factorization
Jiezhong, Qiu, Yuxiao, Dong, Hao, Ma, Jian, Li, Chi, Wang, Kuansan, Wang, Jie, TangWWW 2019
Adversarial Training Methods for Network Embedding
Quanyu, Dai, Xiao, Shen, Liang, Zhang, Qiang, Li, Dan, WangWWW 2019
Iteratively Learning Embeddings and Rules for Knowledge Graph Reasoning
Wen, Zhang, Bibek, Paudel, Liang, Wang, Jiaoyan, Chen, Hai, Zhu, Wei, Zhang, Abraham, Bernstein, Huajun, ChenWWW 2019
Heterogeneous Graph Attention Network
Xiao, Wang, Houye, Ji, Chuan, Shi, Bai, Wang, Peng, Cui, P., Yu, Yanfang, YeWWW 2019
Learning Graph Pooling and Hybrid Convolutional Operations for Text Representations
Hongyang, Gao, Yongjun, Chen, Shuiwang, JiWWW 2019
Dual Graph Attention Networks for Deep Latent Representation of Multifaceted Social Effects in
Qitian, Wu, Hengrui, Zhang, Xiaofeng, Gao, Peng, He, Paul, Weng, Han, Gao, Guihai, ChenWWW 2019Social, recommendation, GAT
Graph Neural Networks for Social Recommendation
Wenqi, Fan, Yao, Ma, Qing, Li, Yuan, He, Eric, Zhao, Jiliang, Tang, Dawei, YinWWW 2019Social, recommendation, GNN
Graphvite: A High-performance Cpu-gpu Hybrid System for Node Embedding
Zhaocheng, Zhu, Shizhen, Xu, Meng, Qu, Jian, TangWWW 2019
Bayesian Graph Convolutional Neural Networks for Semi-supervised Classification
Yingxue, Zhang, Soumyasundar, Pal, Mark, Coates, Deniz, ÜstebayAAAI 2019
Graph Convolutional Networks for Text Classification
Liang, Yao, Chengsheng, Mao, Yuan, LuoAAAI 2019
Multi-task Learning over Graph Structures
Pengfei, Liu, Jie, Fu, Yue, Dong, Xipeng, Qiu, Jackie, Chi, Kit, CheungAAAI 2019
Session-based Recommendation with Graph Neural Networks
Shu, Wu, Yuyuan, Tang, Yanqiao, Zhu, Liang, Wang, Xing, Xie, Tieniu, TanAAAI 2019Session-based, recommendation, GNN
Atomic: an Atlas of Machine Commonsense for If-then Reasoning
Maarten, Sap, Ronan, Le, Bras, Emily, Allaway, Chandra, Bhagavatula, Nicholas, Lourie, Hannah, Rashkin, Brendan, Roof, Noah, A., Smith, Yejin, ChoiAAAI 2019
Mixhop: Higher-order Graph Convolutional Architectures via Sparsified Neighborhood Mixing
Sami, Abu-El-Haija, Bryan, Perozzi, Amol, Kapoor, Nazanin, Alipourfard, Kristina, Lerman, Hrayr, Harutyunyan, Greg, Ver, Steeg, Aram, GalstyanICML 2019
Hongyang, Gao, Shuiwang, JiICML 2019
Disentangled Graph Convolutional Networks
Jianxin, Ma, Peng, Cui, Kun, Kuang, Xin, Wang, Wenwu, ZhuICML 2019
Gmnn: Graph Markov Neural Networks
Meng, Qu, Yoshua, Bengio, Jian, TangICML 2019
Simplifying Graph Convolutional Networks
Felix, Wu, Tianyi, Zhang, Amauri, Holanda, de, Souza, Jr., Christopher, Fifty, Tao, Yu, Kilian, Q., WeinbergerICML 2019
Position-aware Graph Neural Networks
Jiaxuan, You, Rex, Ying, Jure, LeskovecICML 2019
Junhyun, Lee, Inyeop, Lee, Jaewoo, KangICML 2019
Relational Pooling for Graph Representations
Ryan, L., Murphy, Balasubramaniam, Srinivasan, Vinayak, Rao, Bruno, RibeiroICML 2019
Graph Learning Network: A Structure Learning Algorithm
Darwin, Saire, Pilco, Adín, Ramírez, RiveraICML 2019 Workshop
Learning Discrete Structures for Graph Neural Networks
Luca, Franceschi, Mathias, Niepert, Massimiliano, Pontil, Xiao, HeICML 2019
Graphite: Iterative Generative Modeling of Graphs
Aditya, Grover, Aaron, Zweig, Stefano, ErmonICML 2019
Drug-drug Adverse Effect Prediction with Graph Co-attention
Andreea, Deac, Yu-Hsiang, Huang, Petar, Veličković, Pietro, Liò, Jian, TangICML 2019 Workshop
Dag-gnn: Dag Structure Learning with Graph Neural Networks
Yue, Yu, Jie, Chen, Tian, Gao, Mo, YuICML 2019
Continuous Graph Neural Networks
Louis-Pascal, A., C., Xhonneux, Meng, Qu, Jian, TangarXiv 2019
An Efficient Graph Convolutional Network Technique for the Travelling Salesman Problem
Chaitanya, K., Joshi, Thomas, Laurent, Xavier, BressonarXiv 2019
Brain Signal Classification via Learning Connectivity Structure
Soobeom, Jang, Seong-Eun, Moon, Jong-Seok, LeearXiv 2019
Joint Embedding of Structure and Features via Graph Convolutional Networks
Sébastien, Lerique, Jacob, Levy, Abitbol, Márton, KarsaiarXiv 2019
Variational Spectral Graph Convolutional Networks
Louis, Tiao, Pantelis, Elinas, Harrison, Nguyen, Edwin, V., BonillaarXiv 2019
Mario, Krenn, Florian, Häse, AkshatKumar, Nigam, Pascal, Friederich, Alán, Aspuru-GuzikarXiv 2019
Guy, Shtar, Lior, Rokach, Bracha, ShapiraarXiv 2019
Imposing Label-relational Inductive Bias for Extremely Fine-grained Entity Typing
Wenhan, Xiong, Jiawei, Wu, Deren, Lei, Mo, Yu, Shiyu, Chang, Xiaoxiao, Guo, William, Yang, WangNAACL 2019
Single Document Summarization As Tree Induction
Yang, Liu, Ivan, Titov, Mirella, LapataNAACL 2019
Long-tail Relation Extraction via Knowledge Graph Embeddings and Graph Convolution Networks
Ningyu, Zhang, Shumin, Deng, Zhanlin, Sun, Guanying, Wang, Xi, Chen, Wei, Zhang, Huajun, ChenNAACL 2019
Graph-based Global Reasoning Networks
Yunpeng, Chen, Marcus, Rohrbach, Zhicheng, Yan, Shuicheng, Yan, Jiashi, Feng, Yannis, KalantidisCVPR 2019
Deep Graph Laplacian Regularization for Robust Denoising of Real Images
Jin, Zeng, Jiahao, Pang, Wenxiu, Sun, Gene, CheungCVPR 2019
Learning Context Graph for Person Search
Yichao, Yan, Qiang, Zhang, Bingbing, Ni, Wendong, Zhang, Minghao, Xu, Xiaokang, YangCVPR 2019
Graphonomy: Universal Human Parsing via Graph Transfer Learning
Ke, Gong, Yiming, Gao, Xiaodan, Liang, Xiaohui, Shen, Meng, Wang, Liang, LinCVPR 2019
Masked Graph Attention Network for Person Re-identification
Liqiang, Bao, Bingpeng, Ma, Hong, Chang, Xilin, ChenCVPR 2019
Learning to Cluster Faces on an Affinity Graph
Lei, Yang, Xiaohang, Zhan, Dapeng, Chen, Junjie, Yan, Chen, Change, Loy, Dahua, LinCVPR 2019
Actional-structural Graph Convolutional Networks for Skeleton-based Action Recognition
Maosen, Li, Siheng, Chen, Xu, Chen, Ya, Zhang, Yanfeng, Wang, Qi, TianCVPR 2019
Adaptively Connected Neural Networks
Guangrun, Wang, Keze, Wang, Liang, LinCVPR 2019
Reasoning Visual Dialogs with Structural and Partial Observations
Zilong, Zheng, Wenguan, Wang, Siyuan, Qi, Song-Chun, ZhuCVPR 2019
Meshcnn: A Network with an Edge
Rana, Hanocka, Amir, Hertz, Noa, Fish, Raja, Giryes, Shachar, Fleishman, Daniel, Cohen-OrSIGGRAPH 2019h, t, t, p, s, :, /, /, r, a, n, a, h, a, n, o, c, k, a, ., g, i, t, h, u, b, ., i, o, /, M, e, s, h, C, N, N, /
A Neural Influence Diffusion Model for Social Recommendation
Le, Wu, Peijie, Sun, Yanjie, Fu, Richang, Hong, Xiting, Wang, Meng, WangSIGIR 2019Social, Recommendation, diffusion
Neural Graph Collaborative Filtering
Xiang, Wang, Xiangnan, He, Meng, Wang, Fuli, Feng, Tat-Seng, ChuaSIGIR 2019Collaborative, Filtering, GNN
Binarized Collaborative Filtering with Distilling Graph Convolutional Networks
Haoyu, Wang, Defu, Lian, Yong, GeIJCAI 2019
Yu, Li, Hiroyuki, Kuwahara, Peng, Yang, Le, Song, Xin, GaobioRxiv 2019
Identifying Protein-protein Interaction Using Tree Lstm and Structured Attention
Mahtab, Ahmed, Jumayel, Islam, Muhammad, Rifayat, Samee, Robert, E., MercerICSC 2019
Towards Perturbation Prediction of Biological Networks Using Deep Learning
Diya, Li, Jianxi, GaoNature 2019
Graph to Graph: a Topology Aware Approach for Graph Structures Learning and Generation
Mingming, Sun, Ping, LiAISTATS 2019
Pytorch-biggraph: A Large-scale Graph Embedding System
Adam, Lerer, Ledell, Wu, Jiajun, Shen, Timothee, Lacroix, Luca, Wehrstedt, Abhijit, Bose, Alex, PeysakhovichSysML 2019
Aligraph: A Comprehensive Graph Neural Network Platform
Rong, Zhu, Kun, Zhao, Hongxia, Yang, Wei, Lin, Chang, Zhou, Baole, Ai, Yong, Li, Jingren, ZhouVLDB 2019
Learning Attention-based Embeddings for Relation Prediction in Knowledge Graphs
Deepak, Nathani, Jatin, Chauhan, Charu, Sharma, Manohar, KaulACL 2019
Graph Neural Networks with Generated Parameters for Relation Extraction
Hao, Zhu, Yankai, Lin, Zhiyuan, Liu, Jie, Fu, Tat-seng, Chua, Maosong, SunACL 2019
Dynamically Fused Graph Network for Multi-hop Reasoning
Yunxuan, Xiao, Yanru, Qu, Lin, Qiu, Hao, Zhou, Lei, Li, Weinan, Zhang, Yong, YuACL 2019
Encoding Social Information with Graph Convolutional Networks for Political Perspective Detection
Chang, Li, Dan, GoldwasserACL 2019
Attention Guided Graph Convolutional Networks for Relation Extraction
Zhijiang, Guo, Yan, Zhang, Wei, LuACL 2019
Shikhar, Vashishth, Manik, Bhandari, Prateek, Yadav, Piyush, Rai, Chiranjib, Bhattacharyya, Partha, TalukdarACL 2019
Graphrel: Modeling Text As Relational Graphs for Joint Entity and Relation Extraction
Tsu-Jui, Fu, Peng-Hsuan, Li, Wei-Yun, MaACL 2019
Multi-hop Reading Comprehension across Multiple Documents by Reasoning over Heterogeneous Graphs
Ming, Tu, Guangtao, Wang, Jing, Huang, Yun, Tang, Xiaodong, He, Bowen, ZhouACL 2019
Cognitive Graph for Multi-hop Reading Comprehension at Scale
Ming, Ding, Chang, Zhou, Qibin, Chen, Hongxia, Yang, Jie, TangACL 2019
Coherent Comment Generation for Chinese Articles with a Graph-to-sequence Model
Wei, Li, Jingjing, Xu, Yancheng, He, Shengli, Yan, Yunfang, Wu, Xu, SunACL 2019
Matching Article Pairs with Graphical Decomposition and Convolutions
Bang, Liu, Di, Niu, Haojie, Wei, Jinghong, Lin, Yancheng, He, Kunfeng, Lai, Yu, XuACL 2019
Embedding Imputation with Grounded Language Information
Ziyi, Yang, Chenguang, Zhu, Vin, Sachidananda, Eric, DarveACL 2019
Chang, Li, Dan, GoldwasserACL 2019
A Neural Multi-digraph Model for Chinese Ner with Gazetteers
Ruixue, Ding, Pengjun, Xie, Xiaoyan, Zhang, Wei, Lu, Linlin, Li, Luo, SiACL 2019
Tree Communication Models for Sentiment Analysis
Yuan, Zhang, Yue, ZhangACL 2019
A2n: Attending to Neighbors for Knowledge Graph Inference
Trapit, Bansal, Da-Cheng, Juan, Sujith, Ravi, Andrew, McCallumACL 2019
Daesik, Kim, Seonhoon, Kim, Nojun, KwakACL 2019
Yinchuan, Xu, Junlin, YangACL 2019 Workshoph, t, t, p, s, :, /, /, g, i, t, h, u, b, ., c, o, m, /, i, a, n, y, c, x, u, /, R, G, C, N, -, w, i, t, h, -, B, E, R, T
Progan: Network Embedding via Proximity Generative Adversarial Network
Hongchang, Gao, Jian, Pei, Heng, HuangKDD 2019
Learning Network-to-network Model for Content-rich Network Embedding
:authors:` Zhicheng, He, Jie, Liu, Na, Li, Yalou, Huang`KDD 2019
Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks
Srijan, Kumar, Xikun, Zhang, Jure, LeskovecKDD 2019
Graph Representation Learning via Hard and Channel-wise Attention Networks
Hongyang, Gao, Shuiwang, JiKDD 2019
Conditional Random Field Enhanced Graph Convolutional Neural Networks
Hongchang, Gao, Jian, Pei, Heng, HuangKDD 2019
Cluster-gcn: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks
Wei-Lin, Chiang, Xuanqing, Liu, Si, Si, Yang, Li, Samy, Bengio, Cho-Jui, HsiehKDD 2019
Demo-net: Degree-specific Graph Neural Networks for Node and Graph Classification
Jun, Wu, Jingrui, He, Jiejun, XuKDD 2019
Hetgnn: Heterogeneous Graph Neural Network
Chuxu, Zhang, Dongjin, Song, Chao, Huang, Ananthram, Swami, Nitesh, V., ChawlaKDD 2019
Graph Recurrent Networks with Attributed Random Walks
Xiao, Huang, Qingquan, Song, Yuening, Li, Xia, HuKDD 2019
Graph Convolutional Networks with Eigenpooling
Yao, Ma, Suhang, Wang, Charu, Aggarwal, Jiliang, TangKDD 2019
Intentgc: A Scalable Graph Convolution Framework Fusing Heterogeneous Information for Recommendation
Jun, Zhao, Zhou, Zhou, Ziyu, Guan, Wei, Zhao, Wei, Ning, Guang, Qiu, Xiaofei, HeKDD 2019
An End-to-end Neighborhood-based Interaction Model for Knowledge-enhanced Recommendation
Yanru, Qu, Ting, Bai, Weinan, Zhang, Jianyun, Nie, Jian, TangKDD 2019 Workshop
Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks
Namyong, Park, Andrey, Kan, Xin, Luna, Dong, Tong, Zhao, Christos, FaloutsosKDD 2019
Robust Graph Convolutional Networks Against Adversarial Attacks
Dingyuan, Zhu, Ziwei, Zhang, Peng, Cui, Wenwu, ZhuKDD 2019
Certifiable Robustness and Robust Training for Graph Convolutional Networks
Daniel, Zügner, Stephan, GünnemannKDD 2019
Peng, Han, Peng, Yang, Peilin, Zhao, Shuo, Shang, Yong, Liu, Jiayu, Zhou, Xin, Gao, Panos, KalnisKDD 2019
Peng, Han, Peng, Yang, Peilin, Zhao, Shuo, Shang, Yong, Liu, Jiayu, Zhou, Xin, Gao, Panos, KalnisKDD 2019
Deepgcns: Can Gcns Go As Deep As Cnns?
Guohao, Li, Matthias, Muller, Ali, Thabet, Bernard, GhanemICCV 2019
Symmetric Graph Convolutional Autoencoder for Unsupervised Graph Representation Learning
Jiwoong, Park, Minsik, Lee, Hyung, Jin, Chang, Kyuewang, Lee, Jin, Young, ChoiICCV 2019
Pixel2mesh++: Multi-view 3d Mesh Generation via Deformation
Chao, Wen, Yinda, Zhang, Zhuwen, Li, Yanwei, FuICCV 2019
Learning Trajectory Dependencies for Human Motion Prediction
Wei, Mao, Miaomiao, Liu, Mathieu, Salzmann, Hongdong, LiICCV 2019
Graph-based Object Classification for Neuromorphic Vision Sensing
Yin, Bi, Aaron, Chadha, Alhabib, Abbas, Eirina, Bourtsoulatze, Yiannis, AndreopoulosICCV 2019
Fashion Retrieval via Graph Reasoning Networks on a Similarity Pyramid
Zhanghui, Kuang, Yiming, Gao, Guanbin, Li, Ping, Luo, Yimin, Chen, Liang, Lin, Wayne, ZhangICCV 2019
Understanding Human Gaze Communication by Spatio-temporal Graph Reasoning
Lifeng, Fan, Wenguan, Wang, Siyuan, Huang, Xinyu, Tang, Song-Chun, ZhuICCV 2019
Visual Semantic Reasoning for Image-text Matching
Kunpeng, Li, Yulun, Zhang, Kai, Li, Yuanyuan, Li, Yun, FuICCV 2019
Graph Convolutional Networks for Temporal Action Localization
Runhao, Zeng, Wenbing, Huang, Mingkui, Tan, Yu, Rong, Peilin, Zhao, Junzhou, Huang, Chuang, GanICCV 2019
Learning Combinatorial Embedding Networks for Deep Graph Matching
Runzhong, Wang, Junchi, Yan, Xiaokang, YangICCV 2019
Learning to Create Sentence Semantic Relation Graphs for Multi-document Summarization
Diego, Antognini, Boi, FaltingsEMNLP 2019
Dependency-guided Lstm-crf for Named Entity Recognition
Zhanming, Jie, Wei, LuEMNLP 2019
Penghui, Wei, Nan, Xu, Wenji, MaoEMNLP 2019
Dialoguegcn: A Graph Convolutional Neural Network for Emotion Recognition in Conversation
Deepanway, Ghosal, Navonil, Majumder, Soujanya, Poria, Niyati, Chhaya, Alexander, GelbukhEMNLP 2019
Modeling Graph Structure in Transformer for Better Amr-to-text Generation
Jie, Zhu, Junhui, Li, Muhua, Zhu, Longhua, Qian, Min, Zhang, Guodong, ZhouEMNLP 2019
Kagnet: Knowledge-aware Graph Networks for Commonsense Reasoning
Bill, Yuchen, Lin, Xinyue, Chen, Jamin, Chen, Xiang, RenEMNLP 2019
Vgraph: A Generative Model for Joint Community Detection and Node Representation Learning
Fan-Yun, Sun, Meng, Qu, Jordan, Hoffmann, Chin-Wei, Huang, Jian, TangNeurIPS 2019
Variational Graph Recurrent Neural Networks
Ehsan, Hajiramezanali, Arman, Hasanzadeh, Nick, Duffield, Krishna, R, Narayanan, Mingyuan, Zhou, Xiaoning, QianNeurIPS 2019
Social-bigat: Multimodal Trajectory Forecasting Using Bicycle-gan and Graph Attention Networks
Vineet, Kosaraju, Amir, Sadeghian, Roberto, Martín-Martín, Ian, Reid, S., Hamid, Rezatofighi, Silvio, SavareseNeurIPS 2019
Probabilistic Logic Neural Networks for Reasoning
Meng, Qu, Jian, TangNeurIPS 2019
Quaternion Knowledge Graph Embeddings
Shuai, Zhang, Yi, Tay, Lina, Yao, Qi, LiuNeurIPS 2019
Quantum Embedding of Knowledge for Reasoning
Dinesh, Garg, Santosh, K., Srivastava, Hima, KaranamNeurIPS 2019
Multi-relational Poincaré Graph Embeddings
Ivana, Balaževic, Carl, Allen, Timothy, HospedalesNeurIPS 2019
Dfnets: Spectral Cnns for Graphs with Feedback-looped Filters
Asiri, Wijesinghe, Qing, WangNeurIPS 2019
Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology
Nima, Dehmamy, Albert-László, Barabási, Rose, YuNeurIPS 2019
A Flexible Generative Framework for Graph-based Semi-supervised Learning
Jiaqi, Ma, Weijing, Tang, Ji, Zhu, Qiaozhu, MeiNeurIPS 2019
Rethinking Kernel Methods for Node Representation Learning on Graphs
Yu, Tian, Long, Zhao, Xi, Peng, Dimitris, N., MetaxasNeurIPS 2019
Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks
Sitao, Luan, Mingde, Zhao, Xiao-Wen, Chang, Doina, PrecupNeurIPS 2019
N-gram Graph: A Simple Unsupervised Representation for Molecules
Shengchao, Liu, Thevaa, Chandereng, Yingyu, LiangNeurIPS 2019
Semantically-regularized Logic Graph Embeddings
Yaqi, Xie, Ziwei, Xu, Kuldeep, Meel, Mohan, S, Kankanhalli, Harold, SohNeurIPS 2019
Semi-implicit Graph Variational Auto-encoders
Arman, Hasanzadeh, Ehsan, Hajiramezanali, Nick, Duffield, Krishna, Narayanan, Mingyuan, Zhou, Xiaoning, QianNeurIPS 2019
D-vae: A Variational Autoencoder for Directed Acyclic Graphs
Muhan, Zhang, Shali, Jiang, Zhicheng, Cui, Roman, Garnett, Yixin, ChenNeurIPS 2019
No Press Diplomacy: Modeling Multi-agent Gameplay
Philip, Paquette, Yuchen, Lu, Steven, Bocco, Max, O., Smith, Satya, Ortiz-Gagne, Jonathan, K., Kummerfeld, Satinder, Singh, Joelle, Pineau, Aaron, CourvilleNeurIPS 2019
Approximation Ratios of Graph Neural Networks for Combinatorial Problems
Ryoma, Sato, Makoto, Yamada, Hisashi, KashimaNeurIPS 2019
Exact Combinatorial Optimization with Graph Convolutional Neural Networks
Maxime, Gasse, Didier, Chételat, Nicola, Ferroni, Laurent, Charlin, Andrea, LodiNeurIPS 2019
On Learning Paradigms for the Travelling Salesman Problem
Chaitanya, K., Joshi, Thomas, Laurent, Xavier, BressonNeurIPS 2019 Workshop
Learning to Propagate for Graph Meta-learning
Lu, Liu, Tianyi, Zhou, Guodong, Long, Jing, Jiang, Chengqi, ZhangNeurIPS 2019
A Flexible Generative Framework for Graph-based Semi-supervised Learning
Jiaqi, Ma, Weijing, Tang, Ji, Zhu, Qiaozhu, MeiNeurIPS 2019
Jenny, Liu, Aviral, Kumar, Jimmy, Ba, Jamie, Kiros, Kevin, SwerskyNeurIPS 2019
Conditional Structure Generation through Graph Variational Generative Adversarial Nets
Carl, Yang, Peiye, Zhuang, Wenhan, Shi, Alan, Luu, Pan, LiNeurIPS 2019
Efficient Graph Generation with Graph Recurrent Attention Networks
Renjie, Liao, Yujia, Li, Yang, Song, Shenlong, Wang, Charlie, Nash, William, L., Hamilton, David, Duvenaud, Raquel, Urtasun, Richard, ZemelNeurIPS 2019
Graphzoom: A Multi-level Spectral Approach for Accurate and Scalable Graph Embedding
Chenhui, Deng, Zhiqiang, Zhao, Yongyu, Wang, Zhiru, Zhang, Zhuo, FengICLR 2020
Dynamically Pruned Message Passing Networks for Large-scale Knowledge Graph Reasoning
Xiaoran, Xu, Wei, Feng, Yunsheng, Jiang, Xiaohui, Xie, Zhiqing, Sun, Zhi-Hong, DengICLR 2020
Ze, Ye, Kin, Sum, Liu, Tengfei, Ma, Jie, Gao, Chao, ChenICLR 2020
Amir, hosein, Khasahmadi, Kaveh, Hassani, Parsa, Moradi, Leo, Lee, Quaid, MorrisICLR 2020
Strategies for Pre-training Graph Neural Networks
Weihua, Hu, Bowen, Liu, Joseph, Gomes, Marinka, Zitnik, Percy, Liang, Vijay, Pande, Jure, LeskovecICLR 2020
Matthias, Fey, Jan, E., Lenssen, Christopher, Morris, Jonathan, Masci, Nils, M., KriegeICLR 2020
Few-shot Learning on Graphs via Super-classes Based on Graph Spectral Measures
Jatin, Chauhan, Deepak, Nathani, Manohar, KaulICLR 2020
Automated Relational Meta-learning
Huaxiu, Yao, Xian, Wu, Zhiqiang, Tao, Yaliang, Li, Bolin, Ding, Ruirui, Li, Zhenhui, LiICLR 2020
Directional Message Passing for Molecular Graphs
Johannes, Klicpera, Janek, Groß, Stephan, GünnemannICLR 2020
Neural Execution of Graph Algorithms
Petar, Veličković, Rex, Ying, Matilde, Padovano, Raia, Hadsell, Charles, BlundellICLR 2020
Graphaf: a Flow-based Autoregressive Model for Molecular Graph Generation
Chence, Shi, Minkai, Xu, Zhaocheng, Zhu, Weinan, Zhang, Ming, Zhang, Jian, TangICLR 2020
DGL, Team
Luca, Costabello, Sumit, Pai, Chan, Le, Van, Rory, McGrath, Nicholas, McCarthy, Pedro, Tabacof
Alimama, Engineering, Platform, Team, Alimama, Search, Advertising, Algorithm, Team