Yinlin Zhu

According to our database1, Yinlin Zhu authored at least 16 papers between 2023 and 2025.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Other 

Links

On csauthors.net:

Bibliography

2025
Federated Graph Unlearning.
CoRR, August, 2025

FedSA-GCL: A Semi-Asynchronous Federated Graph Learning Framework with Personalized Aggregation and Cluster-Aware Broadcasting.
CoRR, July, 2025

A Comprehensive Data-centric Overview of Federated Graph Learning.
CoRR, July, 2025

Towards Effective Federated Graph Foundation Model via Mitigating Knowledge Entanglement.
CoRR, May, 2025

Rethinking Federated Graph Learning: A Data Condensation Perspective.
CoRR, May, 2025

FedC4: Graph Condensation Meets Client-Client Collaboration for Efficient and Private Federated Graph Learning.
CoRR, April, 2025

Towards Unbiased Federated Graph Learning: Label and Topology Perspectives.
CoRR, April, 2025

Federated Prototype Graph Learning.
CoRR, April, 2025

OpenFGL: A Comprehensive Benchmark for Federated Graph Learning.
Proc. VLDB Endow., January, 2025

Toward Model-centric Heterogeneous Federated Graph Learning: A Knowledge-driven Approach.
CoRR, January, 2025

FedPPD: Towards effective subgraph federated learning via pseudo prototype distillation.
Neural Networks, 2025

2024
Federated Continual Graph Learning.
CoRR, 2024

OpenFGL: A Comprehensive Benchmarks for Federated Graph Learning.
CoRR, 2024

FedTAD: Topology-aware Data-free Knowledge Distillation for Subgraph Federated Learning.
Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

2023
LoyalDE: Improving the performance of Graph Neural Networks with loyal node discovery and emphasis.
Neural Networks, July, 2023

FedGTA: Topology-aware Averaging for Federated Graph Learning.
Proc. VLDB Endow., 2023


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