c-gabri / Federated-Learning-PyTorchLinks
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 prov…
☆79Updated 3 years ago
Alternatives and similar repositories for Federated-Learning-PyTorch
Users that are interested in Federated-Learning-PyTorch are comparing it to the libraries listed below
Sorting:
- FedMD: Heterogenous Federated Learning via Model Distillation☆159Updated 4 years ago
- This is a platform containing the datasets and federated learning algorithms in IoT environments.☆68Updated 11 months ago
- Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints☆180Updated 4 years ago
- An open source FL implement with dataset(Femnist, Shakespeare, MNIST, Cifar-10 and Fashion-Mnist) using pytorch☆132Updated 2 years ago
- PyTorch implementation of Federated Learning with Non-IID Data, and federated learning algorithms, including FedAvg, FedProx.☆122Updated 3 years ago
- Codebase for An Efficient Framework for Clustered Federated Learning.☆120Updated 5 years ago
- Code and data accompanying the FedGen paper☆256Updated last year
- A PyTorch implementation of "Communication-Efficient Learning of Deep Networks from Decentralized Data", AISTATS, 2017☆88Updated last year
- ☆181Updated 2 years ago
- Ditto: Fair and Robust Federated Learning Through Personalization (ICML '21)☆152Updated 3 years ago
- An implementation for "Federated Learning with Non-IID Data via Local Drift Decoupling and Correction"☆88Updated 3 years ago
- Accenture Labs Federated Learning☆106Updated last year
- Official code for "Federated Multi-Task Learning under a Mixture of Distributions" (NeurIPS'21)☆165Updated 3 years ago
- [AAAI'22] FedProto: Federated Prototype Learning across Heterogeneous Clients☆166Updated 3 years ago
- diaoenmao / HeteroFL-Computation-and-Communication-Efficient-Federated-Learning-for-Heterogeneous-Clients[ICLR 2021] HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients☆177Updated 2 years ago
- Standard federated learning implementations in FedLab and FL benchmarks.☆153Updated last year
- [NeurIPS 2019 FL workshop] Federated Learning with Local and Global Representations☆242Updated last year
- PyTorch implementation of FedNova (NeurIPS 2020), and a class of federated learning algorithms, including FedAvg, FedProx.☆223Updated 5 years ago
- [ICML 2022] "DisPFL: Towards Communication-Efficient Personalized Federated learning via Decentralized Sparse Training"☆84Updated 3 years ago
- Implementation of SCAFFOLD: Stochastic Controlled Averaging for Federated Learning☆73Updated 2 years ago
- (NeurIPS 2022) Official Implementation of "Preservation of the Global Knowledge by Not-True Distillation in Federated Learning"☆89Updated 2 years ago
- AAAI 2023 accepted paper, FedALA: Adaptive Local Aggregation for Personalized Federated Learning☆143Updated last year
- ☆81Updated 3 years ago
- Study of data imbalance and asynchronous aggregation algorithm on Federated Learning system (using PySyft)☆62Updated 2 years ago
- fully ready experiments☆39Updated 3 years ago
- Official implementation of "FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective"…☆86Updated 5 years ago
- This is an official implementation for the ICLR2023 paper "The Best of Both Worlds: Accurate Global and Personalized Models through Feder…☆20Updated 9 months ago
- SCAFFOLD and FedAvg implementation☆61Updated 4 years ago
- ☆162Updated 2 years ago
- FedGroup, A Clustered Federated Learning framework based on Tensorflow☆41Updated 4 years ago