Exploiting Neighbor Effect: Conv-Agnostic GNN Framework for Graphs With Heterophily-Reference-Cited by-同舟云学术

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Exploiting Neighbor Effect: Conv-Agnostic GNN Framework for Graphs With Heterophily

Published:2023 Issue: Volume: Page:1-14
ISSN:2162-237X
Container-title:IEEE Transactions on Neural Networks and Learning Systems
language:
Short-container-title:IEEE Trans. Neural Netw. Learning Syst.

Author:

Chen Jie¹^ORCID,Chen Shouzhen¹^ORCID,Gao Junbin²^ORCID,Huang Zengfeng³,Zhang Junping¹^ORCID,Pu Jian⁴^ORCID

Affiliation:

1. Shanghai Key Laboratory of Intelligent Information Processing and the School of Computer Science, Fudan University, Shanghai, China

2. Discipline of Business Analytics, The University of Sydney Business School, The University of Sydney, Camperdown, NSW, Australia

3. School of Data Science, Fudan University, Shanghai, China

4. Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China

Funder

Shanghai Municipal Science and Technology Major Project

National Natural Science Foundation of China

Zhangjiang Laboratory (ZJLab), Shanghai Center for Brain Science and Brain-Inspired Technology

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Software

Link

http://xplorestaging.ieee.org/ielx7/5962385/6104215/10128758.pdf?arnumber=10128758

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1. Permutation Equivariant Graph Framelets for Heterophilous Graph Learning;IEEE Transactions on Neural Networks and Learning Systems;2024-09

2. Learning from Feature and Global Topologies: Adaptive Multi-View Parallel Graph Contrastive Learning;Mathematics;2024-07-21

3. Flow2GNN: Flexible Two-Way Flow Message Passing for Enhancing GNNs Beyond Homophily;IEEE Transactions on Cybernetics;2024

4. Depth-defying OOF-GNN: Sailing smoothly amidst GNN waves;Knowledge-Based Systems;2023-11

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