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• Disentangling, Amplifying, and Debiasing: Learning Disentangled Representations for Fair Graph Neural Networks

  Yeon-Chang Lee, Hojung Shin, Sang-Wook Kim

  12013-12021

  2025-04-11

• Keep the Faith: Faithful Explanations in Convolutional Neural Networks for Case-Based Reasoning

  Tom Nuno Wolf, Fabian Bongratz, Anne-Marie Rickmann, Sebastian Pölsterl, Christian Wachinger

  5921-5929

  2024-03-24

• On Oversquashing in Graph Neural Networks Through the Lens of Dynamical Systems

  Alessio Gravina, Moshe Eliasof, Claudio Gallicchio, Davide Bacciu, Carola-Bibiane Schönlieb

  16906-16914

  2025-04-11

• Efficient On-Chip Learning for Optical Neural Networks Through Power-Aware Sparse Zeroth-Order Optimization

  Jiaqi Gu, Chenghao Feng, Zheng Zhao, Zhoufeng Ying, Ray T. Chen, David Z. Pan

  7583-7591

  2021-05-18

• Adversarial Weight Perturbation Improves Generalization in Graph Neural Networks

  Yihan Wu, Aleksandar Bojchevski, Heng Huang

  10417-10425

  2023-06-26

• Generalization of Graph Neural Networks Is Robust to Model Mismatch

  Zhiyang Wang, Juan Cerviño, Alejandro Ribeiro

  21402-21410

  2025-04-11

• Integrating Co-Training with Edge Discrimination to Enhance Graph Neural Networks Under Heterophily

  Siqi Liu, Dongxiao He, Zhizhi Yu, Di Jin, Zhiyong Feng, Weixiong Zhang

  18960-18968

  2025-04-11

• Enhancing Logical Expressiveness in Graph Neural Networks via Path-Neighbor Aggregation

  Han Yu, Xiaojuan Zhao, Aiping Li, Kai Chen, Ziniu Liu, Zhichao Peng

  27917-27924

  2026-03-14

• HeterGP: Bridging Heterogeneity in Graph Neural Networks with Multi-View Prompting

  Fengyu Yan, Xiaobao Wang, Dongxiao He, Longbiao Wang, Jianwu Dang, Di Jin

  21895-21903

  2025-04-11

• Pre-Training Graph Neural Networks on Molecules by Using Subgraph-Conditioned Graph Information Bottleneck

  Van Thuy Hoang, O-Joun Lee

  17204-17213

  2025-04-11

• Measuring Task Similarity and Its Implication in Fine-Tuning Graph Neural Networks

  Renhong Huang, Jiarong Xu, Xin Jiang, Chenglu Pan, Zhiming Yang, Chunping Wang, Yang Yang

  12617-12625

  2024-03-24

• Feature Variance Regularization: A Simple Way to Improve the Generalizability of Neural Networks

  Ranran Huang, Hanbo Sun, Ji Liu, Lu Tian, Li Wang, Yi Shan, Yu Wang

  4190-4197

  2020-04-03

• Orthogonal Graph Neural Networks

  Kai Guo, Kaixiong Zhou, Xia Hu, Yu Li, Yi Chang, Xin Wang

  3996-4004

  2022-06-28

• Self-Supervised Graph Neural Networks via Diverse and Interactive Message Passing

  Liang Yang, Cheng Chen, Weixun Li, Bingxin Niu, Junhua Gu, Chuan Wang, Dongxiao He, Yuanfang Guo, Xiaochun Cao

  4327-4336

  2022-06-28

• Robust Heterogeneous Graph Neural Networks against Adversarial Attacks

  Mengmei Zhang, Xiao Wang, Meiqi Zhu, Chuan Shi, Zhiqiang Zhang, Jun Zhou

  4363-4370

  2022-06-28

• Learning from the Dark: Boosting Graph Convolutional Neural Networks with Diverse Negative Samples

  Wei Duan, Junyu Xuan, Maoying Qiao, Jie Lu

  6550-6558

  2022-06-28

• Eigenvalue Normalized Recurrent Neural Networks for Short Term Memory

  Kyle Helfrich, Qiang Ye

  4115-4122

  2020-04-03

• Interpreting Unfairness in Graph Neural Networks via Training Node Attribution

  Yushun Dong, Song Wang, Jing Ma, Ninghao Liu, Jundong Li

  7441-7449

  2023-06-26

• Sparse Structure Learning via Graph Neural Networks for Inductive Document Classification

  Yinhua Piao, Sangseon Lee, Dohoon Lee, Sun Kim

  11165-11173

  2022-06-28

• GraLSP: Graph Neural Networks with Local Structural Patterns

  Yilun Jin, Guojie Song, Chuan Shi

  4361-4368

  2020-04-03

• Asymmetric Learning for Spectral Graph Neural Networks

  Fangbing Liu, Qing Wang

  18798-18806

  2025-04-11

• Generating Diagnostic and Actionable Explanations for Fair Graph Neural Networks

  Zhenzhong Wang, Qingyuan Zeng, Wanyu Lin, Min Jiang, Kay Chen Tan

  21690-21698

  2024-03-24

• Unified Graph Neural Networks Pre-training for Multi-domain Graphs

  Mingkai Lin, Xiaobin Hong, Wenzhong Li, Sanglu Lu

  12165-12173

  2025-04-11

• DS-ATGO: Dual-Stage Synergistic Learning via Forward Adaptive Threshold and Backward Gradient Optimization for Spiking Neural Networks

  Jiaqiang Jiang, Wenfeng Xu, Jing Fan, Rui Yan

  1855-1863

  2026-03-14

• Absum: Simple Regularization Method for Reducing Structural Sensitivity of Convolutional Neural Networks

  Sekitoshi Kanai, Yasutoshi Ida, Yasuhiro Fujiwara, Masanori Yamada, Shuichi Adachi

  4394-4403

  2020-04-03