- Compositional Fairness Constraints for Graph Embeddings, Avishek Joey Bose, William L. Hamilton. ICML 2019.
- k-hop Graph Neural Networks, Giannis Nikolentzos, George Dasoulas, Michalis Vazirgiannis. Under NeurIPS 2019 review.
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Mincut pooling in Graph Neural Networks, Filippo Maria Bianchi, Daniele Grattarola, Cesare Alippi.
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Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology, Nima Dehmamy, Albert-László Barabási, Rose Yu. Under NeurIPS 2019 review.
- GraphSAINT: Graph Sampling Based Inductive Learning Method, Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan, Viktor Prasanna. Under NeurIPS 2019 review.
- What graph neural networks cannot learn: depth vs width, Andreas Loukas.
- Graph Representation Learning via Hard and Channel-Wise Attention Networks, Hongyang Gao, Shuiwang Ji. KDD 2019.
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Improving Attention Mechanism in Graph Neural Networks via Cardinality Preservation, Shuo Zhang, Lei Xie. Under NeurIPS 2019 review.
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Dimensional Reweighting Graph Convolutional Networks, Xu Zou, Qiuye Jia, Jianwei Zhang, Chang Zhou, Hongxia Yang, Jie Tang. Under NeurIPS 2019 review.
- dyngraph2vec: Capturing Network Dynamics using Dynamic Graph Representation Learning, Palash Goyal, Sujit Rokka Chhetri, Arquimedes Canedo. Under Knowledge Based Systems review.
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iPool -- Information-based Pooling in Hierarchical Graph Neural Networks, Xing Gao, Hongkai Xiong, Pascal Frossard. Under NeurIPS 2019 review.
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Learning Representations of Graph Data -- A Survey, Mital Kinderkhedia.
- Fisher-Bures Adversary Graph Convolutional Networks, Ke Sun, Piotr Koniusz, Zhen Wang.
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GNN-FiLM: Graph Neural Networks with Feature-wise Linear Modulation, Marc Brockschmidt.
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Certifiable Robustness and Robust Training for Graph Convolutional Networks, Daniel Zügner, Stephan Günnemann. KDD 2019
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Label Efficient Semi-Supervised Learning via Graph Filtering, Qimai Li, Xiao-Ming Wu, Han Liu, Xiaotong Zhang, Zhichao Guan.
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Graph Convolutional Transformer: Learning the Graphical Structure of Electronic Health Records, Edward Choi, Zhen Xu, Yujia Li, Michael W. Dusenberry, Gerardo Flores, Yuan Xue, Andrew M. Dai. Under NeurIPS 2019 review.
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Fast Training of Sparse Graph Neural Networks on Dense Hardware, Matej Balog, Bart van Merriënboer, Subhodeep Moitra, Yujia Li, Daniel Tarlow. Under NeurIPS 2019 review.
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Adversarial Representation Learning on Large-Scale Bipartite Graphs, Chaoyang He, Tian Xie, Yu Rong, Wenbing Huang, Junzhou Huang, Xiang Ren, Cyrus Shahabi. Under NeurIPS 2019 review.
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Inference in Probabilistic Graphical Models by Graph Neural Networks, KiJung Yoon, Renjie Liao, Yuwen Xiong, Lisa Zhang, Ethan Fetaya, Raquel Urtasun, Richard Zemel, Xaq Pitkow. ICML 2019 Workshop
- Provably Powerful Graph Networks, Haggai Maron, Heli Ben-Hamu, Hadar Serviansky, Yaron Lipman. Under NeurIPS 2019 review.
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Simplifying Graph Convolutional Networks, Felix Wu, Tianyi Zhang, Amauri Holanda de Souza Jr., Christopher Fifty, Tao Yu, Kilian Q. Weinberger. ICML 2019
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A Graph Auto-Encoder for Attributed Network Embedding, Keting Cen, Huawei Shen, Jinhua Gao, Qi Cao, Bingbing Xu, Xueqi Cheng.
- XLNet: Generalized Autoregressive Pretraining for Language Understanding, Zhilin Yang∗, Zihang Dai∗, Yiming Yang, Jaime Carbonell, Ruslan Salakhutdinov, Quoc V. Le. Under NeurIPS 2019 review.
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vGraph: A Generative Model for Joint Community Detection and Node Representation Learning, Fan-Yun Sun, Meng Qu, Jordan Hoffmann, Chin-Wei Huang, Jian Tang.
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Consistency of semi-supervised learning algorithms on graphs: Probit and one-hot methods, Franca Hoffmann, Bamdad Hosseini, Zhi Ren, Andrew M. Stuart.
- Homogeneous Network Embedding for Massive Graphs via Personalized PageRank, Renchi Yang, Jieming Shi, Xiaokui Xiao, Sourav S. Bhowmick, Yin Yang.
- Attributed Graph Clustering: A Deep Attentional Embedding Approach, Chun Wang, Shirui Pan, Ruiqi Hu, Guodong Long, Jing Jiang, Chengqi Zhang.
- Disentangling Mixtures of Epidemics on Graphs, Jessica Hoffmann, Soumya Basu, Surbhi Goel, Constantine Caramanis. Under NeurIPS 2019 review.
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Cognitive Knowledge Graph Reasoning for One-shot Relational Learning, Zhengxiao Du, Chang Zhou, Ming Ding, Hongxia Yang, Jie Tang. Under NeurIPS 2019 review.
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Identifying Illicit Accounts in Large Scale E-payment Networks -- A Graph Representation Learning Approach, Da Sun Handason Tam, Wing Cheong Lau, Bin Hu, Qiu Fang Ying, Dah Ming Chiu, Hong Liu.
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Utilizing Edge Features in Graph Neural Networks via Variational Information Maximization, Pengfei Chen, Weiwen Liu, Chang-Yu Hsieh, Guangyong Chen, Shengyu Zhang. Under NeurIPS 2019 review.
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Position-aware Graph Neural Networks, Jiaxuan You, Rex Ying, Jure Leskovec. ICML 2019
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Weight Agnostic Neural Networks, Adam Gaier, David Ha. Under NeurIPS 2019 review.
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Graph Embedding on Biomedical Networks: Methods, Applications, and Evaluations, Xiang Yue, Zhen Wang, Jingong Huang, Srinivasan Parthasarathy, Soheil Moosavinasab, Yungui Huang, Simon M. Lin, Wen Zhang, Ping Zhang, Huan Sun. Under Bioinformatics journal review.
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Multiple instance learning with graph neural networks, Ming Tu, Jing Huang, Xiaodong He, Bowen Zhou. ICML 2019 Workshop.
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Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations, Francesco Locatello, Stefan Bauer, Mario Lucic, Gunnar Rätsch, Sylvain Gelly, Bernhard Schölkopf, Olivier Bachem. ICML 2019 best paper award
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Graph Convolutional Transformer: Learning the Graphical Structure of Electronic Health Records, Edward Choi, Zhen Xu, Yujia Li, Michael W. Dusenberry, Gerardo Flores, Yuan Xue, Andrew M. Dai. Under NeurIPS 2019 review.
- Topology Attack and Defense for Graph Neural Networks: An Optimization Perspective, Kaidi Xu, Hongge Chen, Sijia Liu, Pin-Yu Chen, Tsui-Wei Weng, Mingyi Hong, Xue Lin. IJCAI 2019
- Fine-grained Event Categorization with Heterogeneous Graph Convolutional Networks, Hao Peng, Jianxin Li, Qiran Gong, Yangqiu Song, Yuanxing Ning, Kunfeng Lai, Philip S. Yu. IJCAI 2019
- Labeled Graph Generative Adversarial Networks, Shuangfei Fan, Bert Huang. Under NeurIPS 2019 review.
- Dynamically Fused Graph Network for Multi-hop Reasoning, Yunxuan Xiao, Yanru Qu, Lin Qiu, Hao Zhou, Lei Li, Weinan Zhang, Yong Yu. ACL 19.
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Break the Ceiling: Stronger Multi-scale Deep Graph Convolutional Networks, Sitao Luan, Mingde Zhao, Xiao-Wen Chang, Doina Precup. Under NeurIPS 2019 review.
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Can Graph Neural Networks Help Logic Reasoning?, Yuyu Zhang, Xinshi Chen, Yuan Yang, Arun Ramamurthy, Bo Li, Yuan Qi, Le Song. Under NeurIPS 2019 review.
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GRAM: Scalable Generative Models for Graphs with Graph Attention Mechanism, Wataru Kawai, Yusuke Mukuta, Tatsuya Harada. Under NeurIPS 2019 review.
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Variational Spectral Graph Convolutional Networks, Louis Tiao, Pantelis Elinas, Harrison Nguyen, Edwin V. Bonilla. Under NeurIPS 2019 review.
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Binarized Collaborative Filtering with Distilling Graph Convolutional Networks, Haoyu Wang, Defu Lian, Yong Ge.
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DEMO-Net: Degree-specific Graph Neural Networks for Node and Graph Classification, Jun Wu, Jingrui He, Jiejun Xu. KDD 2019 Research Track.
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Graph Learning Network: A Structure Learning Algorithm, Darwin Saire Pilco, Adín Ramírez Rivera. ICML 2019 Workshop.
- Factor Graph Neural Network, Zhen Zhang, Fan Wu, Wee Sun Lee. Under NeurIPS 2019 review.
- Pre-training of Graph Augmented Transformers for Medication Recommendation, Junyuan Shang, Tengfei Ma, Cao Xiao, Jimeng Sun. IJCAI 2019.
- Pre-Training Graph Neural Networks for Generic Structural Feature Extraction, Ziniu Hu, Changjun Fan, Ting Chen, Kai-Wei Chang, Yizhou Sun. Under NeurIPS 2019 review.
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Graph Neural Tangent Kernel: Fusing Graph Neural Networks with Graph Kernels, Simon S. Du, Kangcheng Hou, Barnabás Póczos, Ruslan Salakhutdinov, Ruosong Wang, Keyulu Xu.
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EdMot: An Edge Enhancement Approach for Motif-aware Community Detection, Pei-Zhen Li, Ling Huang, Chang-Dong Wang, Jian-Huang Lai. KDD 2019
- Pre-training Graph Neural Networks, Weihua Hu*, Bowen Liu*, Joseph Gomes, Marinka Zitnik, Percy Liang, Vijay S. Pande, Jure Leskovec. Under NeurIPS 2019 review.