Showing 6 open source projects for "apache framework"

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  • 1
    Flower

    Flower

    Flower: A Friendly Federated Learning Framework

    A unified approach to federated learning, analytics, and evaluation. Federate any workload, any ML framework, and any programming language. Federated learning systems vary wildly from one use case to another. Flower allows for a wide range of different configurations depending on the needs of each individual use case. Flower originated from a research project at the University of Oxford, so it was built with AI research in mind. Many components can be extended and overridden to build new...
    Downloads: 3 This Week
    Last Update:
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  • 2
    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: 0 This Week
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  • 3
    Substra

    Substra

    Low-level Python library used to interact with a Substra network

    An open-source framework supporting privacy-preserving, traceable federated learning and machine learning orchestration. Offers a Python SDK, high-level FL library (SubstraFL), and web UI to define datasets, models, tasks, and orchestrate secure, auditable collaborations.
    Downloads: 2 This Week
    Last Update:
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  • 4
    FATE

    FATE

    An industrial grade federated learning framework

    FATE (Federated AI Technology Enabler) is the world's first industrial grade federated learning open source framework to enable enterprises and institutions to collaborate on data while protecting data security and privacy. It implements secure computation protocols based on homomorphic encryption and multi-party computation (MPC). Supporting various federated learning scenarios, FATE now provides a host of federated learning algorithms, including logistic regression, tree-based algorithms,...
    Downloads: 0 This Week
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  • 5
    Xfl

    Xfl

    An Efficient and Easy-to-use Federated Learning Framework

    XFL is a lightweight, high-performance federated learning framework supporting both horizontal and vertical FL. It integrates homomorphic encryption, DP, secure MPC, and optimizes network resilience. Compatible with major ML libraries and deployable via Docker or Conda.
    Downloads: 2 This Week
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  • 6
    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: 3 This Week
    Last Update:
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