Python for《Deep Learning》，该书为《深度学习》(花书) 数学推导、原理剖析与源码级别代码实现

Flower: A Friendly Federated AI Framework

37 traditional FL (tFL) or personalized FL (pFL) algorithms, 3 scenarios, and 24 datasets. www.pfllib.com/

Implementation of Communication-Efficient Learning of Deep Networks from Decentralized Data

[ICLR 2021] HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients

This is the official repository for “Drone-based RGB-Infrared Cross-Modality Vehicle Detection via Uncertainty-Aware Learning” (IEEE T-CSVT 2022).

FedAvg code with privacy protection function, the application of Paillier homomorphic encryption algorithm and differential privacy, differential privacy includes Laplacian mechanism differential p…

An implementation of Secure Aggregation algorithm based on "Practical Secure Aggregation for Privacy-Preserving Machine Learning (Bonawitz et. al)" in Python.

[ICML 2022] "DisPFL: Towards Communication-Efficient Personalized Federated learning via Decentralized Sparse Training"

Preserve data privacy with k-anonymity (samarati & mondrian), differential privacy, federated learning, paillier homomorphic encryption, etc.

Multi-Agent Graph Convolutional Reinforcement Learning for Dynamic Electric Vehicle Charging Pricing

A secure aggregation system for private federated learning

Chain-PPFL: A Privacy-Preserving Federated Learning Framework based on Chained SMC

Code for Part-Guided Attention Learning for Vehicle Instance Retrieval (TITS2020). A strong Vehicle Re-ID model with part region guidance.

FL-TP: Federated Learning-based Vehicle Trajectory Prediction Algorithm against Cyberattacks

[ACM EuroSys'24] Dordis: Efficient Federated Learning with Dropout-Resilient Differential Privacy

The source code of the paper "Efficient Privacy-Preserving Federated Learning with Compressed Sensing"

FedShare: Secure Aggregation based on Additive Secret Sharing in Federated Learning

Aggregation Service for Federated Learning: An Efficient, Secure, and More Resilient Realization

Offical code for the paper "Turning Privacy-preserving Mechanisms against Federated Learning" accepted at ACM Conference on Computer and Communications Security (CCS) 2023

Batch authentication with fedrated learnig

Federated Learning on Non-IID Data Silos: An Experimental Study (ICDE 2022)

The origin of the Non-IID phenomenon is the personalization of users, who generate the Non-IID data. With Non-IID (Not Independent and Identically Distributed) issues existing in the federated lear…