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    FL4Health

    FL4Health

    Library to facilitate federated learning research

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    Downloads: 6 This Week
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    Pfl Research

    Pfl Research

    Simulation framework for accelerating research

    A fast, modular Python framework released by Apple for privacy-preserving federated learning (PFL) simulation. Integrates with TensorFlow, PyTorch, and classical ML, and offers high-speed distributed simulation (7–72× faster than alternatives).
    Downloads: 1 This Week
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    Appfl

    Appfl

    Advanced Privacy-Preserving Federated Learning framework

    APPFL (Advanced Privacy-Preserving Federated Learning) is a Python framework enabling researchers to easily build and benchmark privacy-aware federated learning solutions. It supports flexible algorithm development, differential privacy, secure communications, and runs efficiently on HPC and multi-GPU setups.
    Downloads: 5 This Week
    Last Update:
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    FedLab

    FedLab

    A flexible Federated Learning Framework based on PyTorch

    A Python-based framework for federated learning simulation, emphasizing modularity, communication efficiency, and algorithmic flexibility. Supports both server- and client-side customization for research and development purposes.
    Downloads: 0 This Week
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    Retool your internal operations

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