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Code for "Towards Geometry-Consistent Federated Graph Learning" accepted by WWW 2026.

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GeoFed

Environment Requirements

Python Version

  • Python 3.8+

Required Packages

  • PyTorch 1.12+
  • PyTorch Geometric 2.0+
  • NumPy
  • SciPy
  • scikit-learn
  • scikit-network
  • pymetis
  • geoopt
  • tqdm

Installation

pip install torch torch-geometric numpy scipy scikit-learn scikit-network pymetis geoopt tqdm

Quick Start

Basic Usage

python main.py

Configuration

The main configuration is set in main.py. You can modify the following parameters:

  • args.dataset: Dataset to use (e.g., "sbm", "Cora", "CiteSeer")
  • args.simulation_mode: Data partitioning method ("subgraph_fl_louvain" or "subgraph_fl_metis_plus")
  • args.num_clients: Number of federated clients
  • args.num_rounds: Number of federated learning rounds

Notes

  • The project uses CUDA by default. Set args.use_cuda = False in main.py if you want to use CPU only.
  • Dataset files should be placed in the dataset/ directory.

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Code for "Towards Geometry-Consistent Federated Graph Learning" accepted by WWW 2026.

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