Robust Graph Structure Learning under Heterophily
Fuente:
arXiv
Saved in:
| Main Authors: | Xie, Xuanting, Kang, Zhao, Chen, Wenyu |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Disentangling Homophily and Heterophily in Multimodal Graph Clustering
by: Guo, Zhaochen, et al.
Published: (2025)
by: Guo, Zhaochen, et al.
Published: (2025)
Provable Filter for Real-world Graph Clustering
by: Xie, Xuanting, et al.
Published: (2024)
by: Xie, Xuanting, et al.
Published: (2024)
Aggregation-aware MLP: An Unsupervised Approach for Graph Message-passing
by: Xie, Xuanting, et al.
Published: (2025)
by: Xie, Xuanting, et al.
Published: (2025)
Attention Beyond Neighborhoods: Reviving Transformer for Graph Clustering
by: Xie, Xuanting, et al.
Published: (2025)
by: Xie, Xuanting, et al.
Published: (2025)
Graph Contrastive Learning under Heterophily via Graph Filters
by: Yang, Wenhan, et al.
Published: (2023)
by: Yang, Wenhan, et al.
Published: (2023)
Simplified PCNet with Robustness
by: Li, Bingheng, et al.
Published: (2024)
by: Li, Bingheng, et al.
Published: (2024)
HeterSEED: Semantics-Structure Decoupling for Heterogeneous Graph Learning under Heterophily
by: Li, Xinyi, et al.
Published: (2026)
by: Li, Xinyi, et al.
Published: (2026)
One Node One Model: Featuring the Missing-Half for Graph Clustering
by: Xie, Xuanting, et al.
Published: (2024)
by: Xie, Xuanting, et al.
Published: (2024)
When Heterophily Meets Heterogeneous Graphs: Latent Graphs Guided Unsupervised Representation Learning
by: Shen, Zhixiang, et al.
Published: (2024)
by: Shen, Zhixiang, et al.
Published: (2024)
HeRB: Heterophily-Resolved Structure Balancer for Graph Neural Networks
by: Chen, Ke-Jia, et al.
Published: (2025)
by: Chen, Ke-Jia, et al.
Published: (2025)
CDC: A Simple Framework for Complex Data Clustering
by: Kang, Zhao, et al.
Published: (2024)
by: Kang, Zhao, et al.
Published: (2024)
Structure-Guided Input Graph for GNNs facing Heterophily
by: Tenorio, Victor M., et al.
Published: (2024)
by: Tenorio, Victor M., et al.
Published: (2024)
Understanding Heterophily for Graph Neural Networks
by: Wang, Junfu, et al.
Published: (2024)
by: Wang, Junfu, et al.
Published: (2024)
Exploring Heterophily in Graph-level Tasks
by: Hou, Qinhan, et al.
Published: (2025)
by: Hou, Qinhan, et al.
Published: (2025)
Graph Neural Networks for Graphs with Heterophily: A Survey
by: Zheng, Xin, et al.
Published: (2022)
by: Zheng, Xin, et al.
Published: (2022)
GMoPE:A Prompt-Expert Mixture Framework for Graph Foundation Models
by: Wang, Zhibin, et al.
Published: (2025)
by: Wang, Zhibin, et al.
Published: (2025)
Learn from Heterophily: Heterophilous Information-enhanced Graph Neural Network
by: Zheng, Yilun, et al.
Published: (2024)
by: Zheng, Yilun, et al.
Published: (2024)
Heterophily-Aware Graph Attention Network
by: Wang, Junfu, et al.
Published: (2023)
by: Wang, Junfu, et al.
Published: (2023)
Adaptive Heterogeneous Graph Neural Networks: Bridging Heterophily and Heterogeneity
by: Chen, Qin, et al.
Published: (2025)
by: Chen, Qin, et al.
Published: (2025)
Incorporating Heterophily into Graph Neural Networks for Graph Classification
by: Yang, Jiayi, et al.
Published: (2022)
by: Yang, Jiayi, et al.
Published: (2022)
Addressing Graph Heterogeneity and Heterophily from A Spectral Perspective
by: Lu, Kangkang, et al.
Published: (2024)
by: Lu, Kangkang, et al.
Published: (2024)
On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks
by: Zhu, Jiong, et al.
Published: (2024)
by: Zhu, Jiong, et al.
Published: (2024)
Self-attention Dual Embedding for Graphs with Heterophily
by: Lai, Yurui, et al.
Published: (2023)
by: Lai, Yurui, et al.
Published: (2023)
Resurrecting Label Propagation for Graphs with Heterophily and Label Noise
by: Cheng, Yao, et al.
Published: (2023)
by: Cheng, Yao, et al.
Published: (2023)
A Generative Model for Controllable Feature Heterophily in Graphs
by: Wang, Haoyu, et al.
Published: (2025)
by: Wang, Haoyu, et al.
Published: (2025)
Heterophily-informed Message Passing
by: Wang, Haishan, et al.
Published: (2025)
by: Wang, Haishan, et al.
Published: (2025)
Revisiting Graph-Based Fraud Detection in Sight of Heterophily and Spectrum
by: Xu, Fan, et al.
Published: (2023)
by: Xu, Fan, et al.
Published: (2023)
Modeling Heterophily in Multiplex Graphs: An Adaptive Approach for Node Classification
by: Abdous, Kamel, et al.
Published: (2026)
by: Abdous, Kamel, et al.
Published: (2026)
A Label-Free Heterophily-Guided Approach for Unsupervised Graph Fraud Detection
by: Pan, Junjun, et al.
Published: (2025)
by: Pan, Junjun, et al.
Published: (2025)
Learning Directed Acyclic Graphs from Partial Orderings
by: Shojaie, Ali, et al.
Published: (2024)
by: Shojaie, Ali, et al.
Published: (2024)
Graph Negative Feedback Bias Correction Framework for Adaptive Heterophily Modeling
by: Lv, Jiaqi, et al.
Published: (2026)
by: Lv, Jiaqi, et al.
Published: (2026)
Oversmoothing, Oversquashing, Heterophily, Long-Range, and more: Demystifying Common Beliefs in Graph Machine Learning
by: Arnaiz-Rodriguez, Adrian, et al.
Published: (2025)
by: Arnaiz-Rodriguez, Adrian, et al.
Published: (2025)
DiRW: Path-Aware Digraph Learning for Heterophily
by: Su, Daohan, et al.
Published: (2024)
by: Su, Daohan, et al.
Published: (2024)
A Survey on Learning from Graphs with Heterophily: Recent Advances and Future Directions
by: Gong, Chenghua, et al.
Published: (2024)
by: Gong, Chenghua, et al.
Published: (2024)
Heterophily-Aware Fair Recommendation using Graph Convolutional Networks
by: Gholinejad, Nemat, et al.
Published: (2024)
by: Gholinejad, Nemat, et al.
Published: (2024)
Cheeger--Hodge Contrastive Learning for Structurally Robust Graph Representation Learning
by: Zhao, Mengyang, et al.
Published: (2026)
by: Zhao, Mengyang, et al.
Published: (2026)
Leveraging Personalized PageRank and Higher-Order Topological Structures for Heterophily Mitigation in Graph Neural Networks
by: Wang, Yumeng, et al.
Published: (2025)
by: Wang, Yumeng, et al.
Published: (2025)
Aligning the Spectrum: Hybrid Graph Pre-training and Prompt Tuning across Homophily and Heterophily
by: Luo, Haitong, et al.
Published: (2025)
by: Luo, Haitong, et al.
Published: (2025)
DuoGNN: Topology-aware Graph Neural Network with Homophily and Heterophily Interaction-Decoupling
by: Mancini, K., et al.
Published: (2024)
by: Mancini, K., et al.
Published: (2024)
When Heterophily Meets Heterogeneity: Challenges and a New Large-Scale Graph Benchmark
by: Lin, Junhong, et al.
Published: (2024)
by: Lin, Junhong, et al.
Published: (2024)
Similar Items
-
Disentangling Homophily and Heterophily in Multimodal Graph Clustering
by: Guo, Zhaochen, et al.
Published: (2025) -
Provable Filter for Real-world Graph Clustering
by: Xie, Xuanting, et al.
Published: (2024) -
Aggregation-aware MLP: An Unsupervised Approach for Graph Message-passing
by: Xie, Xuanting, et al.
Published: (2025) -
Attention Beyond Neighborhoods: Reviving Transformer for Graph Clustering
by: Xie, Xuanting, et al.
Published: (2025) -
Graph Contrastive Learning under Heterophily via Graph Filters
by: Yang, Wenhan, et al.
Published: (2023)