facebookresearch / FLSimLinks
Federated Learning Simulator (FLSim) is a flexible, standalone core library that simulates FL settings with a minimal, easy-to-use API. FLSim is domain-agnostic and accommodates many use cases such as vision and text.
☆263Updated last year
Alternatives and similar repositories for FLSim
Users that are interested in FLSim are comparing it to the libraries listed below
Sorting:
- A collection of Google research projects related to Federated Learning and Federated Analytics.☆736Updated 4 months ago
- FedScale is a scalable and extensible open-source federated learning (FL) platform.☆402Updated last year
- Privacy Preserving Vertical Federated Learning☆219Updated 2 years ago
- A library for federated learning (a distributed machine learning process) in an enterprise environment.☆519Updated last month
- Leaf: A Benchmark for Federated Settings☆888Updated 2 years ago
- A large labelled image dataset for benchmarking in federated learning☆102Updated last year
- Breaching privacy in federated learning scenarios for vision and text☆307Updated 2 months ago
- diaoenmao / HeteroFL-Computation-and-Communication-Efficient-Federated-Learning-for-Heterogeneous-Clients[ICLR 2021] HeteroFL: Computation and Communication Efficient Federated Learning for Heterogeneous Clients☆174Updated 2 years ago
- FedTorch is a generic repository for benchmarking different federated and distributed learning algorithms using PyTorch Distributed API.☆193Updated 6 months ago
- [NeurIPS 2019 FL workshop] Federated Learning with Local and Global Representations☆242Updated last year
- FedJAX is a JAX-based open source library for Federated Learning simulations that emphasizes ease-of-use in research.☆266Updated 3 months ago
- Plato: A Research Framework for Federated Learning☆384Updated this week
- resources about federated learning and privacy in machine learning☆540Updated last year
- Handy PyTorch implementation of Federated Learning (for your painless research)☆455Updated last year
- DP-FTRL from "Practical and Private (Deep) Learning without Sampling or Shuffling" for centralized training.☆31Updated 4 months ago
- Personalized Federated Learning with Moreau Envelopes (pFedMe) using Pytorch (NeurIPS 2020)☆303Updated 3 years ago
- Implementation of dp-based federated learning framework using PyTorch☆310Updated 2 years ago
- Federated Optimization in Heterogeneous Networks (MLSys '20)☆697Updated 2 years ago
- ☆174Updated last year
- A Simulator for Privacy Preserving Federated Learning☆96Updated 4 years ago
- Code for Federated Learning with Matched Averaging, ICLR 2020.☆340Updated 3 years ago
- Fair Resource Allocation in Federated Learning (ICLR '20)☆250Updated last year
- 📦 Collect some Asynchronous Federated Learning papers.☆117Updated last year
- Advanced Privacy-Preserving Federated Learning framework☆154Updated this week
- PyTorch for benchmarking communication-efficient distributed SGD optimization algorithms☆78Updated 4 years ago
- Official code for "Federated Multi-Task Learning under a Mixture of Distributions" (NeurIPS'21)☆163Updated 2 years ago
- PyTorch implementation of FedNova (NeurIPS 2020), and a class of federated learning algorithms, including FedAvg, FedProx.☆222Updated 5 years ago
- Algorithms to recover input data from their gradient signal through a neural network☆305Updated 2 years ago
- SRDS 2020: End-to-End Evaluation of Federated Learning and Split Learning for Internet of Things☆114Updated 4 years ago
- Standard federated learning implementations in FedLab and FL benchmarks.☆153Updated last year