weimingwill / EasyFLLinks
An easy-to-use federated learning platform
☆301Updated 2 years ago
Alternatives and similar repositories for EasyFL
Users that are interested in EasyFL are comparing it to the libraries listed below
Sorting:
- Personalized federated learning codebase for research☆407Updated 2 years ago
- Code and data accompanying the FedGen paper☆257Updated last year
- Model-Contrastive Federated Learning (CVPR 2021)☆298Updated 3 years ago
- ☆182Updated 2 years ago
- Standard federated learning implementations in FedLab and FL benchmarks.☆153Updated last year
- AAAI 2023 accepted paper, FedALA: Adaptive Local Aggregation for Personalized Federated Learning☆145Updated last year
- Federated Learning Benchmark - Federated Learning on Non-IID Data Silos: An Experimental Study (ICDE 2022)☆611Updated last year
- Overview of Federal Learning☆293Updated 2 years ago
- [AAAI'22] FedProto: Federated Prototype Learning across Heterogeneous Clients☆170Updated 3 years ago
- PyTorch implementation of FedNova (NeurIPS 2020), and a class of federated learning algorithms, including FedAvg, FedProx.☆226Updated 5 years ago
- Ditto: Fair and Robust Federated Learning Through Personalization (ICML '21)☆155Updated 3 years ago
- Heterogeneous Federated Learning: State-of-the-art and Research Challenges☆168Updated last year
- Personalized Federated Learning with Moreau Envelopes (pFedMe) using Pytorch (NeurIPS 2020)☆306Updated 3 years ago
- On the Convergence of FedAvg on Non-IID Data☆274Updated 3 years ago
- Official code for "Federated Multi-Task Learning under a Mixture of Distributions" (NeurIPS'21)☆165Updated 3 years ago
- [NeurIPS 2019 FL workshop] Federated Learning with Local and Global Representations☆244Updated last year
- Clustered Federated Learning: Model-Agnostic Distributed Multi-Task Optimization under Privacy Constraints☆184Updated 4 years ago
- PyTorch Federated Learning (easy to use and extend)☆296Updated 2 years ago
- PyTorch implementation of FedProx (Federated Optimization for Heterogeneous Networks, MLSys 2020).☆112Updated 3 years ago
- ☆179Updated last year
- A PyTorch implementation of "Communication-Efficient Learning of Deep Networks from Decentralized Data", AISTATS, 2017☆90Updated last year
- 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☆178Updated 7 months ago
- Implementation of dp-based federated learning framework using PyTorch☆314Updated 2 weeks ago
- PyTorch implementation of Federated Learning with Non-IID Data, and federated learning algorithms, including FedAvg, FedProx.☆122Updated 3 years ago
- FedMD: Heterogenous Federated Learning via Model Distillation☆160Updated 4 years ago
- You only need to configure one file to support model heterogeneity. Consistent GPU memory usage for single or multiple clients.☆221Updated last month
- An implementation for "Federated Learning with Non-IID Data via Local Drift Decoupling and Correction"☆88Updated 3 years ago
- Official code implementation for "Personalized Federated Learning using Hypernetworks" [ICML 2021]☆196Updated 2 years ago
- Implement FedAvg algorithm based on Tensorflow☆266Updated 5 years ago
- Everything you want about DP-Based Federated Learning, including Papers and Code. (Mechanism: Laplace or Gaussian, Dataset: femnist, shak…☆417Updated last year