Benchmark of federated learning. Dedicated to the community. 🤗

Personalized federated learning codebase for research

Personalized Federated Learning with Moreau Envelopes (pFedMe) using Pytorch (NeurIPS 2020)

Official code for "Federated Multi-Task Learning under a Mixture of Distributions" (NeurIPS'21)

联邦学习模块化框架，支持各类FL。A universal federated learning framework, free to switch thread and process modes

PyTorch implementation of Layer-wised Model Aggregation for Personalized Federated Learning

PyTorch Implementation of Personalized federated learning with theoretical guarantees: A model-agnostic meta-learning approach

Official code for "Personalized Federated Learning through Local Memorization" (ICML'22)

(SIGKDD 2022) Connected Low-Loss Subspace Learning for a Personalization in Federated Learning (https://arxiv.org/abs/2109.07628)

[NeurIPS 2023] Adaptive Test-Time Personalization for Federated Learning. Wenxuan Bao, Tianxin Wei, Haohan Wang, Jingrui He.

[ICML 2023] Optimizing the Collaboration Structure in Cross-Silo Federated Learning. Wenxuan Bao, Haohan Wang, Jun Wu, Jingrui He.

PyTorch Implementation of Federated Reconstruction: Partially Local Federated Learning

SemiPFL: Personalized Semi-Supervised Federated Learning Framework for Edge Intelligence

[ACSAC '24] FedCAP: Robust Federated Learning via Customized Aggregation and Personalization

Personalized Federated Learning with Parameter Propagation

Assessing Academic Performance: Personalized Federated Learning for Identifying Overperforming and Underperforming Schools and Individual-Level Implications

Exploring Different Personalization Mechanisms for Federated Time Series Forecasting