FedGraph / fedgraph
FedGraph (Federated Graph) is a library built upon PyTorch to easily train Graph Neural Networks (GNNs) under federated (distributed) setting.
☆19Updated this week
Related projects ⓘ
Alternatives and complementary repositories for fedgraph
- Code for Subgraph Federated Learning with Missing Neighbor Generation (NeurIPS 2021)☆71Updated 2 years ago
- ☆16Updated this week
- Official Code for FedGCN [NeurIPS 2023]☆59Updated 6 months ago
- Official implementation of "Graph Unlearning" (ACM CCS 2022)☆38Updated last year
- This repository aims to provide links to works about privacy attacks and privacy preservation on graph data with Graph Neural Networks (G…☆22Updated last year
- GAP: Differentially Private Graph Neural Networks with Aggregation Perturbation (USENIX Security '23)☆44Updated last year
- This repository is the implementation of Federated Graph Classification over Non-IID Graphs.☆39Updated last year
- Official Code Repository for the paper - Personalized Subgraph Federated Learning (ICML 2023)☆44Updated last year
- [AAAI'23] Federated Learning on Non-IID Graphs via Structural Knowledge Sharing☆58Updated last year
- FedGraphNN: A Federated Learning Platform for Graph Neural Networks with MLOps Support. The previous research version is accepted to ICLR…☆180Updated 10 months ago
- Source code for Learn Locally Correct Globally☆14Updated 2 years ago
- ☆21Updated 2 years ago
- Paper List for Fair Graph Learning (FairGL).☆132Updated last month
- Certified (approximate) machine unlearning for simplified graph convolutional networks (SGCs) with theoretical guarantees (ICLR 2023)☆19Updated last year
- ☆12Updated last year
- ☆29Updated last year
- Locally Private Graph Neural Networks (ACM CCS 2021)☆45Updated last year
- An official PyTorch implementation of "Unnoticeable Backdoor Attacks on Graph Neural Networks" (WWW 2023)