• Best Paper Award Yangkun Wang, Jiarui Jin, Weinan Zhang, Yong Yu, Zheng Zhang and David Wipf. Bag of Tricks for Node Classification with Graph Neural Networks[Link]
• Best Student Paper Award Kachun Lo and Tsukasa Ishigaki. HANABI: Graph Embedding for Recommendation via Conditional Proximity.[Link]
• Vijay Lingam, Rahul Ragesh, Arun Iyer and Sundararajan Sellamanickam. Simple Truncated SVD based Model for Node Classification on Heterophilic Graphs.[Link]
• Heng Chang, Yu Rong, Tingyang Xu, Wenbing Huang, Somayeh Sojoudi, Junzhou Huang and Wenwu Zhu. Spectral Graph Attention Network with Fast Eigen-approximation.[Link]
• Ben Finkelshtein, Chaim Baskin, Evgenii Zheltonozhskii and Uri Alon. Single-Node Attack for Fooling Graph Neural Networks.[Link]
• Ana Lucic, Maartje ter Hoeve, Gabriele Tolomei, Maarten de Rijke and Fabrizio Silvestri. Counterfactual Explanations for Graph Neural Networks.[Link]
• Mingqi Yang, Renjian Wang, Yanming Shen, Heng Qi and Baocai Yin. On the Design of Powerful Aggregations in Graph Neural Networks.[Link]
• Zonghan Wu, Da Zheng, Shirui Pan, Quan Gan, Guodong Long and George Karypis. Learning spatial-temporal dependencies via a unified graph neural network.[Link]
• Juncheng Liu, Yiwei Wang and Bryan Hooi. LSCALE: Latent Space Clustering-Based Active Learning for Node Classification.[Link]
• Lanning Wei, Huan Zhao and Zhiqiang He. Learn Layer-wise Connections in Graph Neural Networks.[Link]
• Chaoyang He, Emir Ceyani, Keshav Balasubramanian, Murali Annavaram and Salman Avestimehr. SpreadGNN: Serverless Multi-task Federated Learning for Graph Neural Networks.[Link]
• Daheng Wang, Tong Zhao, Nitesh Chawla and Meng Jiang. Evolutionary Graph Normalizing Flows.[Link]
• Hejie Cui, Zijie Lu, Pan Li and Carl Yang. On Positional and Structural Node Features for Graph Neural Networks on Featureless Graphs.[Link]
• Yanqiao Zhu, Yichen Xu, Hejie Cui, Carl Yang, Qiang Liu and Shu Wu. Structure-Aware Hard Negative Mining for Heterogeneous Graph Contrastive Learning.[Link]
• Xiang Ling, Lingfei Wu, Saizhuo Wang, Tengfei Ma, Fangli Xu, Alex X. Liu, Chunming Wu and Shouling Ji. Multi-Level Graph Matching Networks for Deep Graph Similarity Learning.[Link]
• Yongqi Zhang and Quanming Yao. RED-GNN: Knowledge Graph Reasoning with Relational Directed Graph.[Link]
• Jinhui Pang, Huinan Xu, Yan Zhang and Yan Yuan. A New Event-knowledge Representation Approach Based on Behavior Base.[Link]
• Seema Nagar, Sameer Gupta, Bahushruth Cs, Ferdous Barbhuiya and Kuntal Dey. Hate Speech Detection on Social Media Using Graph Convolutional Networks.[Link]
• Lucas G. S. Jeub, Marya Bazzi, Mihai Cucuringu, Giovanni Colavizza and Xiaowen Dong. Local2Global: Scaling global representation learning on graphs via local training.[Link]
• Cory Scott, Eric Mjolsness, Diane Oyen, Chie Kodera, Magalie Uyttewaal and David Bouchez. Diff2Dist: Differentiable Graph Diffusion Distance.[Link]