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Condensing Graphs via One-Step Gradient Matching. Wei Jin, Xianfeng Tang, Haoming Jiang, Zheng Li, Danqing Zhang, Jiliang Tang, Bing Yin.
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Diffusion Models for Graphs Benefit From Discrete State Spaces. Kilian Konstantin Haefeli, Karolis Martinkus, Nathanaël Perraudin, Roger Wattenhofer.
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How Powerful is Implicit Denoising in Graph Neural Networks. Songtao Liu, Zhitao Ying, Hanze Dong, Lu Lin, Jinghui Chen, Dinghao Wu.
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GraphCG: Unsupervised Discovery of Steerable Factors in Graphs. Shengchao Liu, Chengpeng Wang, Weili Nie, Hanchen Wang, Jiarui Lu, Bolei Zhou, Jian Tang.
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Spectrum Guided Topology Augmentation for Graph Contrastive Learning. Lu Lin, Jinghui Chen, Hongning Wang.
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Provably expressive temporal graph networks. Amauri H Souza, Diego Mesquita, Samuel Kaski, Vikas Garg.
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A New Graph Node Classification Benchmark: Learning Structure from Histology Cell Graphs. Claudia Vanea, Jonathan Campbell, Omri Dodi, Liis Salumäe, Karen Meir, Drorith Hochner, Hagit Hochner, Triin Laisk, Linda M Ernst, Cecilia Lindgren, Christoffer Nellaker.
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Faster Hyperparameter Search on Graphs via Calibrated Dataset Condensation. Mucong Ding, Xiaoyu Liu, Tahseen Rabbani, Furong Huang.
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Complete the Missing Half: Augmenting Aggregation Filtering with Diversification for Graph Convolutional Networks. Sitao Luan, Mingde Zhao, Chenqing Hua, Xiao-Wen Chang, Doina Precup.
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ACMP: Allen-Cahn Message Passing with Attractive and Repulsive Forces for Graph Neural Networks. Yuelin Wang, Kai Yi, Xinliang Liu, Yu Guang Wang, Shi Jin.
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COIN: Co-Cluster Infomax for Bipartite Graphs. Baoyu Jing, Yuchen Yan, Yada Zhu, Hanghang Tong.
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Empowering Language Models with Knowledge Graph Reasoning for Question Answering. Ziniu Hu, Yichong Xu, Wenhao Yu, Shuohang Wang, Ziyi Yang, Chenguang Zhu, Kai-Wei Chang, Yizhou Sun.
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On the Unreasonable Effectiveness of Feature Propagation in Learning on Graphs with Missing Node Features. Emanuele Rossi, Henry Kenlay, Maria I. Gorinova, Benjamin Paul Chamberlain, Xiaowen Dong, Michael M. Bronstein.
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A deep learning approach to recover conditional independence graphs. Harsh Shrivastava, Urszula Chajewska, Robin Abraham, Xinshi Chen.
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Differentially Private Graph Learning via Sensitivity-Bounded Personalized PageRank. Alessandro Epasto, Vahab Mirrokni, Bryan Perozzi, Anton Tsitsulin, Peilin Zhong.
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A Simple Hypergraph Kernel Convolution based on Discounted Markov Diffusion Process. Fuyang Li, Jiying Zhang, Xi Xiao, bin zhang, Dijun Luo.
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New Frontiers in Graph Autoencoders: Joint Community Detection and Link Prediction. Guillaume Salha-Galvan, Johannes F. Lutzeyer, George Dasoulas, Romain Hennequin, Michalis Vazirgiannis.
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Certified Graph Unlearning. Eli Chien, Chao Pan, Olgica Milenkovic.
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antGLasso: An Efficient Tensor Graphical Lasso Algorithm. Bailey Andrew, David Westhead, Luisa Cutillo.
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Expectation Complete Graph Representations using Graph Homomorphisms. Maximilian Thiessen, Pascal Welke, Thomas Gärtner.
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A Graph Is More Than Its Nodes: Towards Structured Uncertainty-Aware Learning on Graphs. Hans Hao-Hsun Hsu, Yuesong Shen, Daniel Cremers.
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Learning Heterogeneous Interaction Strengths by Trajectory Prediction with Graph Neural Network. Seungwoong Ha, Hawoong Jeong.
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GraphFramEx: Towards Systematic Evaluation of Explainability Methods for Graph Neural Networks. Kenza Amara, Zhitao Ying, Zitao Zhang, Zhihao Han, Yinan Shan, Ulrik Brandes, Sebastian Schemm.
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NOSMOG: Learning Noise-robust and Structure-aware MLPs on Graphs. Yijun Tian, Chuxu Zhang, Zhichun Guo, Xiangliang Zhang, Nitesh Chawla.
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Equivariant Graph Hierarchy-based Neural Networks. Jiaqi Han, Yu Rong, Tingyang Xu, Wenbing Huang.
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Efficient Automatic Machine Learning via Design Graphs. Ying-Xin Wu, Jiaxuan You, Jure Leskovec, Zhitao Ying.
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Invertible Neural Networks for Graph Prediction. Chen Xu, Xiuyuan Cheng, Yao Xie.
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Diving into Unified Data-Model Sparsity for Class-Imbalanced Graph Representation Learning. Chunhui Zhang, Chao Huang, Yijun Tian, Qianlong Wen, Zhongyu Ouyang, Youhuan Li, Yanfang Ye, Chuxu Zhang.
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Shift-Robust Node Classification via Graph Clustering Co-training. Qi Zhu, Chao Zhang, Chanyoung Park, Carl Yang, Jiawei Han.
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Contrastive Graph Few-Shot Learning. Chunhui Zhang, Hongfu Liu, Jundong Li, Yanfang Ye, Chuxu Zhang.
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Variational Graph Auto-Encoders for Heterogeneous Information Network. Abhishek Dalvi, Ayan Acharya, Jing Gao, Vasant G Honavar.
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Modeling Hierarchical Topological Structure in Scientific Images with Graph Neural Networks. Samuel Leventhal, Attila Gyulassy, Valerio Pascucci, Mark Heimann.
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SPGP: Structure Prototype Guided Graph Pooling. Sangseon Lee, Dohoon Lee, Yinhua Piao, Sun Kim.
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Individual Fairness in Dynamic Financial Networks. Zixing Song, Yueen Ma, Irwin King.
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AutoTransfer: AutoML with Knowledge Transfer - An Application to Graph Neural Networks. Kaidi Cao, Jiaxuan You, Jiaju Liu, Jure Leskovec.
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Skeleton Clustering: Graph-Based Approach for Dimension-Free Density-Aided Clustering. Zeyu Wei, Yen-Chi Chen.
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Graph Contrastive Learning with Cross-view Reconstruction. Qianlong Wen, Zhongyu Ouyang, Chunhui Zhang, Yiyue Qian, Yanfang Ye, Chuxu Zhang.
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Neural Coarsening Process for Multi-level Graph Combinatorial Optimization. Hyeonah Kim, Minsu Kim, Changhyun Kwon, Jinkyoo Park.
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GIST: Distributed Training for Large-Scale Graph Convolutional Networks. Cameron R. Wolfe, Jingkang Yang, Fangshuo Liao, Arindam Chowdhury, Chen Dun, Artun Bayer, Santiago Segarra, Anastasios Kyrillidis.
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Modular Flows: Differential Molecular Generation. Yogesh Verma, Samuel Kaski, Markus Heinonen, Vikas Garg.
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GLINKX: A Scalable Unified Framework for Homophilous and Heterophilous Graphs. Marios Papachristou, Rishab Goel, Frank Portman, Matthew Miller, Rong Jin.
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Synthetic Graph Generation to Benchmark Graph Learning. John Palowitch, Anton Tsitsulin, Bryan Perozzi, Brandon A. Mayer.
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Improving Graph Neural Networks at Scale: Combining Approximate PageRank and CoreRank. Ariel Ricardo Ramos Vela, Johannes F. Lutzeyer, Anastasios Giovanidis, Michalis Vazirgiannis.
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pyGSL: A Graph Structure Learning Toolkit. Max Wasserman, Gonzalo Mateos.
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From Local to Global: Spectral-Inspired Graph Neural Networks. Ningyuan Teresa Huang, Soledad Villar, Carey Priebe, Da Zheng, Chengyue Huang, Lin Yang, Vladimir Braverman.
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Multimodal Video Understanding using Graph Neural Network. Ayush Singh, Vikram Gupta.
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Hierarchical Abstraction for Combinatorial Generalization in Object Rearrangement. Michael Chang, Alyssa Li Dayan, Franziska Meier, Thomas L. Griffiths, Sergey Levine, Amy Zhang.
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Convolutional Neural Networks on Manifolds: From Graphs and Back. Zhiyang Wang, Luana Ruiz, Alejandro Ribeiro.
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Dissimilar Nodes Improve Graph Active Learning. Zhicheng Ren, Yifu Yuan, Yuxin Wu, Xiaxuan Gao, YEWEN WANG, Yizhou Sun.
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Agent-based Graph Neural Networks. Karolis Martinkus, Pál András Papp, Benedikt Schesch, Roger Wattenhofer.
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PolarMOT: How far can geometric relations take us in 3D multi-object tracking?. Aleksandr Kim, Guillem Braso, Aljosa Osep, Laura Leal-Taixé.
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Sequence-Graph Duality: Unifying User Modeling with Self-Attention for Sequential Recommendation. Zeren Shui, Ge Liu, Anoop Deoras, George Karypis.
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Graph Neural Networks for Selection of Preconditioners and Krylov Solvers. Ziyuan Tang, Hong Zhang, Jie Chen.
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Sketch-GNN: Scalable Graph Neural Networks with Sublinear Training Complexity. Mucong Ding, Tahseen Rabbani, Bang An, Evan Z Wang, Furong Huang.
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