"node representation learning" Papers
14 papers found
Conference
Discrete Curvature Graph Information Bottleneck
Xingcheng Fu, Jian Wang, Yisen Gao et al.
AAAI 2025paperarXiv:2412.19993
3
citations
GRAIN: Multi-Granular and Implicit Information Aggregation Graph Neural Network for Heterophilous Graphs
Songwei Zhao, Yuan Jiang, Zijing Zhang et al.
AAAI 2025paperarXiv:2504.06649
3
citations
Normalize Then Propagate: Efficient Homophilous Regularization for Few-Shot Semi-Supervised Node Classification
Baoming Zhang, MingCai Chen, Jianqing Song et al.
AAAI 2025paperarXiv:2501.08581
1
citations
Self-supervised Masked Graph Autoencoder via Structure-aware Curriculum
Haoyang Li, Xin Wang, Zeyang Zhang et al.
ICML 2025spotlight
Automated Loss function Search for Class-imbalanced Node Classification
Xinyu Guo, KAI WU, Xiaoyu Zhang et al.
ICML 2024arXiv:2405.14133
2
citations
Cooperative Graph Neural Networks
Ben Finkelshtein, Xingyue Huang, Michael Bronstein et al.
ICML 2024arXiv:2310.01267
52
citations
Deep Structural Knowledge Exploitation and Synergy for Estimating Node Importance Value on Heterogeneous Information Networks
Yankai Chen, Yixiang Fang, Qiongyan Wang et al.
AAAI 2024paperarXiv:2402.12411
14
citations
FairSIN: Achieving Fairness in Graph Neural Networks through Sensitive Information Neutralization
Cheng Yang, Jixi Liu, Yunhe Yan et al.
AAAI 2024paperarXiv:2403.12474
33
citations
Mitigating Oversmoothing Through Reverse Process of GNNs for Heterophilic Graphs
MoonJeong Park, Jaeseung Heo, Dongwoo Kim
ICML 2024arXiv:2403.10543
6
citations
On Which Nodes Does GCN Fail? Enhancing GCN From the Node Perspective
Jincheng Huang, Jialie SHEN, Xiaoshuang Shi et al.
ICML 2024
Perfect Alignment May be Poisonous to Graph Contrastive Learning
Jingyu Liu, Huayi Tang, Yong Liu
ICML 2024arXiv:2310.03977
4
citations
Rethinking Graph Masked Autoencoders through Alignment and Uniformity
Liang Wang, Xiang Tao, Qiang Liu et al.
AAAI 2024paperarXiv:2402.07225
32
citations
Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning on Heterophilic Graphs
Langzhang Liang, Sunwoo Kim, Kijung Shin et al.
ICML 2024arXiv:2405.20652
13
citations
Towards Inductive Robustness: Distilling and Fostering Wave-Induced Resonance in Transductive GCNs against Graph Adversarial Attacks
Ao Liu, Wenshan Li, Tao Li et al.
AAAI 2024paperarXiv:2312.08651
7
citations