idyllic990920

FedAPEN

This repository contains the official implementation of the paper entitled with "FedAPEN: Personalized Cross-silo Federated Learning with Adaptability to Statistical Heterogeneity".

FedRolex

[NeurIPS 2022] "FedRolex: Model-Heterogeneous Federated Learning with Rolling Sub-Model Extraction" by Samiul Alam, Luyang Liu, Ming Yan, and Mi Zhang

PeFLL

pFedHN

Official code implementation for "Personalized Federated Learning using Hypernetworks" [ICML 2021]

classifier-balancing

This repository contains code for the paper "Decoupling Representation and Classifier for Long-Tailed Recognition", published at ICLR 2020

FedRepo

pFedLA

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

paper_response_to_reviewers

The template of LaTeX files for the response to the reviewers

FedPAC

Simplified Implementation of FedPAC

FL-bench

Benchmark of federated learning. Dedicated to the community. 🤗

EasyTemporalPointProcess

EasyTPP: Towards Open Benchmarking Temporal Point Processes

fedsage

Code for Subgraph Federated Learning with Missing Neighbor Generation (NeurIPS 2021)

FedEgo

GCN-PyTorch

Graph Convolution Network for PyTorch

PFLlib

We expose this user-friendly algorithm library (with an integrated evaluation platform) for beginners who intend to start federated learning (FL) study

Federated-Mutual-Learning

Pytorch_FedMD

Data-Free-Adversarial-Distillation

Code and pretrained models for paper: Data-Free Adversarial Distillation

pytorch-grad-cam

Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

zsdb3kd

Knowledge distillation (KD) from a decision-based black-box (DB3) teacher without training data.

2018-IJCAI-top3

This 2018 IJCAI alimama Top3 Code

Federated-Learning-PyTorch

PyTorch implementation of Federated Learning algorithms FedSGD, FedAvg, FedAvgM, FedIR, FedVC, FedProx and standard SGD, applied to visual classification. Client distributions are synthesized with arbitrary non-identicalness and imbalance (Dirichlet priors). Client systems can be arbitrarily heterogeneous. Several mobile-friendly models are provided

HeteroFL-Computation-and-Communication-Efficient-Federated-Learning-for-Heterogeneous-Clients

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

Awesome-Federated-Machine-Learning

Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond

Awesome-Federated-Learning

FedML - The Research and Production Integrated Federated Learning Library: https://fedml.ai

SKA

FedGen

Code and data accompanying the FedGen paper

ZeroShotKnowledgeTransfer

Accompanying code for the paper "Zero-shot Knowledge Transfer via Adversarial Belief Matching"

Efficient-Computing

Efficient computing methods developed by Huawei Noah's Ark Lab

Awesome-Data-Free-Knowledge-Distillation

Data-Free Knowledge Distillation