iQua / flsim
A simulation framework for Federated Learning written in PyTorch
☆203Updated 2 years ago
Alternatives and similar repositories for flsim:
Users that are interested in flsim are comparing it to the libraries listed below
- On the Convergence of FedAvg on Non-IID Data☆259Updated 2 years ago
- D-DQN Reinforcement Learning for device selection in Federated Learning☆41Updated last year
- Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints☆165Updated 3 years ago
- Implementation of paper "Client-Edge-Cloud Hierarchical Federated Learning☆119Updated 4 years ago
- Implement FedAvg algorithm based on Tensorflow☆240Updated 4 years ago
- A PyTorch implementation of "Communication-Efficient Learning of Deep Networks from Decentralized Data", AISTATS, 2017☆78Updated 7 months ago
- Standard federated learning implementations in FedLab and FL benchmarks.☆155Updated last year
- PyTorch implementation of FedNova (NeurIPS 2020), and a class of federated learning algorithms, including FedAvg, FedProx.☆209Updated 4 years ago
- FedTorch is a generic repository for benchmarking different federated and distributed learning algorithms using PyTorch Distributed API.☆189Updated 10 months ago
- Official code for "Federated Multi-Task Learning under a Mixture of Distributions" (NeurIPS'21)☆158Updated 2 years ago
- Personalized Federated Learning with Moreau Envelopes (pFedMe) using Pytorch (NeurIPS 2020)☆293Updated 2 years ago
- [NeurIPS 2019 FL workshop] Federated Learning with Local and Global Representations☆230Updated 7 months ago
- Releasing the source code Version1.☆144Updated 3 years ago
- ☆93Updated 3 years ago
- Fair Resource Allocation in Federated Learning (ICLR '20)☆246Updated last year
- Ditto: Fair and Robust Federated Learning Through Personalization (ICML '21)☆139Updated 2 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☆158Updated 2 years ago
- Codebase for An Efficient Framework for Clustered Federated Learning.☆112Updated 4 years ago
- ☆31Updated 2 years ago
- Accenture Labs Federated Learning☆97Updated 11 months ago
- ☆174Updated last year
- PyTorch implementation of Federated Learning with Non-IID Data, and federated learning algorithms, including FedAvg, FedProx.☆118Updated 2 years ago
- Code and data accompanying the FedGen paper☆250Updated 4 months ago
- 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☆159Updated last month
- [ICML 2022] "DisPFL: Towards Communication-Efficient Personalized Federated learning via Decentralized Sparse Training"☆76Updated 2 years ago
- FedMD: Heterogenous Federated Learning via Model Distillation☆151Updated 3 years ago
- Code for paper "Adaptive Federated Learning in Resource Constrained Edge Computing Systems"☆264Updated 4 months ago
- Unofficial Pytorch implementation of "Federated Meta-Learning with Fast Convergence and Efficient Communication"☆74Updated 4 years ago
- PyTorch implementation of FedProx (Federated Optimization for Heterogeneous Networks, MLSys 2020).☆102Updated 2 years ago
- Active Client Selection for Federated Learning☆43Updated last year