FGL studies

Here we present a summary of papers in the FGL field.

Graph-FL

Title	Venue	Year	Materials
Federated Graph Cl assification over Non-IID Graphs	NeurIPS	2021	[Paper ] [Code]
Federated Learning on Non-IID Graphs via Structural Knowledge Sharing	AAAI	2023	[Paper] [Code]

Subgraph-FL

Title	Venue	Year	Materials
Subgraph Federated Learning with Missing Neighbor Generation	NeurIPS	2021	[Paper ] [Code]
FedGSL: Federated Graph Structure Learning for Local Subgraph Augmentation	ICBD	2022	[Paper]
Federated Node Cl assification over Graphs with Latent Link-type H eterogeneity	WWW	2023	[Paper] [Code]
FedHGN: a federated framework for h eterogeneous graph neural networks	IJCAI	2023	[Paper] [Code]
Federated graph semantic and structural learning	IJCAI	2023	[Paper] [Code]
Globally Consistent Federated Graph Autoencoder for Non-IID Graphs	IJCAI	2023	[Paper] [Code]
AdaFGL: A New Paradigm for Federated Node Cl assification with Topology H eterogeneity	ICDE	2024	[Paper] [Code]
FedGTA: To pology-aware Averaging for Federated Graph Learning	VLDB	2024	[Paper] [Code]
Federated Graph Learning under Domain Shift with G eneralizable Prototypes	AAAI	2024	[Paper] [Code]
FedGT: Federated Node Cl assification with Scalable Graph Transformer	arXiv	2024	[Paper]
FedGL: Federated graph learning framework with global self -supervision	IS	2024	[Pape r]
Deep Efficient Private Neighbor Generation for Subgraph Federated Learning	SDM	2024	[Paper]

Survey / Library / Benchmarks

Title	Venue	Year	Materials
Federated graph learning–a position paper	arXiv	2021	[Paper]
FedGraphNN: A Federated Learning System and Benchmark for Graph Neural Networks	arXiv	2021	[Paper] ` [Code] <https://github.co m/FedML-AI/FedGraphNN>`__
Federated graph machine learning: A survey of concepts, techniques, and applications	SIGKDD	2022	[Paper]
Federat edscope-gnn: Towards a unified, c omprehensive and efficient package for federated graph learning	KDD	2022	[Paper] [Co de]
Federated Graph Neural Networks: Overview, Techniques, and Challenges	TNNLS	2024	[Paper]