google / fedjax
FedJAX is a JAX-based open source library for Federated Learning simulations that emphasizes ease-of-use in research.
☆257Updated 3 months ago
Alternatives and similar repositories for fedjax:
Users that are interested in fedjax are comparing it to the libraries listed below
- Federated Learning Simulator (FLSim) is a flexible, standalone core library that simulates FL settings with a minimal, easy-to-use API. F…☆257Updated 6 months ago
- Federated Learning Utilities and Tools for Experimentation☆187Updated last year
- A collection of Google research projects related to Federated Learning and Federated Analytics.☆708Updated 7 months ago
- Algorithms for Privacy-Preserving Machine Learning in JAX☆93Updated 9 months ago
- Breaching privacy in federated learning scenarios for vision and text☆281Updated 11 months ago
- autodp: A flexible and easy-to-use package for differential privacy☆272Updated last year
- Privacy Preserving Vertical Federated Learning☆217Updated last year
- A large labelled image dataset for benchmarking in federated learning☆95Updated last year
- A Simulator for Privacy Preserving Federated Learning☆93Updated 4 years ago
- Differentially Private Optimization for PyTorch 👁🙅♀️☆184Updated 4 years ago
- Code for fast dpsgd implementations in JAX/TF☆59Updated 2 years ago
- SOON TO BE DEPRECATED - The TensorFlow bindings for PySyft☆57Updated 4 years ago
- FEDn: An enterprise-ready open source federated learning framework. This repository contains the Python framework, CLI and API.☆152Updated this week
- A library for federated learning (a distributed machine learning process) in an enterprise environment.☆504Updated last year
- A codebase that makes differentially private training of transformers easy.☆171Updated 2 years ago
- Fast, memory-efficient, scalable optimization of deep learning with differential privacy☆115Updated 2 months ago
- A fast algorithm to optimally compose privacy guarantees of differentially private (DP) mechanisms to arbitrary accuracy.☆73Updated last year
- ☆80Updated 2 years ago
- FedTorch is a generic repository for benchmarking different federated and distributed learning algorithms using PyTorch Distributed API.☆190Updated 10 months ago
- resources about federated learning and privacy in machine learning☆531Updated 8 months ago
- Leaf: A Benchmark for Federated Settings☆873Updated last year
- A set of tutorials to implement the Federated Averaging algorithm on TensorFlow.☆182Updated 3 years ago
- Decentralized SGD and Consensus with Communication Compression: https://arxiv.org/abs/1907.09356☆66Updated 4 years ago
- Algorithms to recover input data from their gradient signal through a neural network☆284Updated last year
- Simulation framework for accelerating research in Private Federated Learning☆318Updated last month
- Federated posterior averaging implemented in JAX☆51Updated last year
- PyTorch for benchmarking communication-efficient distributed SGD optimization algorithms☆75Updated 3 years ago
- The Python Differential Privacy Library. Built on top of: https://github.com/google/differential-privacy☆508Updated 6 months ago
- PriMIA: Privacy-preserving Medical Image Analysis☆130Updated last year
- Code for Federated Learning with Matched Averaging, ICLR 2020.☆335Updated 3 years ago