:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autori principali:	Chen, Ke-Jia, Mu, Wenhui, Liu, Zheng
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning
Accesso online:	https://arxiv.org/abs/2504.17276
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Graph Neural Networks for Graphs with Heterophily: A Survey
di: Zheng, Xin, et al.
Pubblicazione: (2022)

Understanding Heterophily for Graph Neural Networks
di: Wang, Junfu, et al.
Pubblicazione: (2024)

Learn from Heterophily: Heterophilous Information-enhanced Graph Neural Network
di: Zheng, Yilun, et al.
Pubblicazione: (2024)

HeGMN: Heterogeneous Graph Matching Network for Learning Graph Similarity
di: Sang, Shilong, et al.
Pubblicazione: (2025)

Adaptive Heterogeneous Graph Neural Networks: Bridging Heterophily and Heterogeneity
di: Chen, Qin, et al.
Pubblicazione: (2025)

Incorporating Heterophily into Graph Neural Networks for Graph Classification
di: Yang, Jiayi, et al.
Pubblicazione: (2022)

Robust Graph Structure Learning under Heterophily
di: Xie, Xuanting, et al.
Pubblicazione: (2024)

On the Impact of Feature Heterophily on Link Prediction with Graph Neural Networks
di: Zhu, Jiong, et al.
Pubblicazione: (2024)

Exploring Heterophily in Graph-level Tasks
di: Hou, Qinhan, et al.
Pubblicazione: (2025)

Heterophily-Aware Graph Attention Network
di: Wang, Junfu, et al.
Pubblicazione: (2023)

HeterSEED: Semantics-Structure Decoupling for Heterogeneous Graph Learning under Heterophily
di: Li, Xinyi, et al.
Pubblicazione: (2026)

Structure-Guided Input Graph for GNNs facing Heterophily
di: Tenorio, Victor M., et al.
Pubblicazione: (2024)

Leveraging Personalized PageRank and Higher-Order Topological Structures for Heterophily Mitigation in Graph Neural Networks
di: Wang, Yumeng, et al.
Pubblicazione: (2025)

A Label-Free Heterophily-Guided Approach for Unsupervised Graph Fraud Detection
di: Pan, Junjun, et al.
Pubblicazione: (2025)

DuoGNN: Topology-aware Graph Neural Network with Homophily and Heterophily Interaction-Decoupling
di: Mancini, K., et al.
Pubblicazione: (2024)

Heterophily-Agnostic Hypergraph Neural Networks with Riemannian Local Exchanger
di: Sun, Li, et al.
Pubblicazione: (2026)

Graph Contrastive Learning under Heterophily via Graph Filters
di: Yang, Wenhan, et al.
Pubblicazione: (2023)

Heterophily-Aware Fair Recommendation using Graph Convolutional Networks
di: Gholinejad, Nemat, et al.
Pubblicazione: (2024)

Self-attention Dual Embedding for Graphs with Heterophily
di: Lai, Yurui, et al.
Pubblicazione: (2023)

Addressing Graph Heterogeneity and Heterophily from A Spectral Perspective
di: Lu, Kangkang, et al.
Pubblicazione: (2024)

How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashing
di: Huang, Keke, et al.
Pubblicazione: (2024)

A Generative Model for Controllable Feature Heterophily in Graphs
di: Wang, Haoyu, et al.
Pubblicazione: (2025)

Resurrecting Label Propagation for Graphs with Heterophily and Label Noise
di: Cheng, Yao, et al.
Pubblicazione: (2023)

Disentangling Homophily and Heterophily in Multimodal Graph Clustering
di: Guo, Zhaochen, et al.
Pubblicazione: (2025)

Heterophily-informed Message Passing
di: Wang, Haishan, et al.
Pubblicazione: (2025)

Modeling Heterophily in Multiplex Graphs: An Adaptive Approach for Node Classification
di: Abdous, Kamel, et al.
Pubblicazione: (2026)

Rethinking Structure Learning For Graph Neural Networks
di: Zheng, Yilun, et al.
Pubblicazione: (2024)

Graph Negative Feedback Bias Correction Framework for Adaptive Heterophily Modeling
di: Lv, Jiaqi, et al.
Pubblicazione: (2026)

Resolving Node Identifiability in Graph Neural Processes via Laplacian Spectral Encodings
di: Yan, Zimo, et al.
Pubblicazione: (2025)

Revisiting Graph-Based Fraud Detection in Sight of Heterophily and Spectrum
di: Xu, Fan, et al.
Pubblicazione: (2023)

Eddy-Resolving Global Ocean Forecasting with Multi-Scale Graph Neural Networks
di: Hirabayashi, Yuta, et al.
Pubblicazione: (2026)

When Heterophily Meets Heterogeneous Graphs: Latent Graphs Guided Unsupervised Representation Learning
di: Shen, Zhixiang, et al.
Pubblicazione: (2024)

Aligning the Spectrum: Hybrid Graph Pre-training and Prompt Tuning across Homophily and Heterophily
di: Luo, Haitong, et al.
Pubblicazione: (2025)

Characterizing Graph Datasets for Node Classification: Homophily-Heterophily Dichotomy and Beyond
di: Platonov, Oleg, et al.
Pubblicazione: (2022)

GraphPI: Efficient Protein Inference with Graph Neural Networks
di: Ma, Zheng, et al.
Pubblicazione: (2026)

When Heterophily Meets Heterogeneity: Challenges and a New Large-Scale Graph Benchmark
di: Lin, Junhong, et al.
Pubblicazione: (2024)

View-based Explanations for Graph Neural Networks
di: Chen, Tingyang, et al.
Pubblicazione: (2024)

A Survey on Learning from Graphs with Heterophily: Recent Advances and Future Directions
di: Gong, Chenghua, et al.
Pubblicazione: (2024)

Oversmoothing, Oversquashing, Heterophily, Long-Range, and more: Demystifying Common Beliefs in Graph Machine Learning
di: Arnaiz-Rodriguez, Adrian, et al.
Pubblicazione: (2025)

Probability Passing for Graph Neural Networks: Graph Structure and Representations Joint Learning
di: Wang, Ziyan, et al.
Pubblicazione: (2024)