CENTAUR-Privacy-Federated-Representation-Learning
Federated Learning Framework
A framework for Federated Learning with Differential Privacy using PyTorch
A PyTorch based repository for Federate Learning with Differential Privacy
13 stars
3 watching
2 forks
Language: Shell
last commit: over 1 year ago Related projects:
Repository | Description | Stars |
---|---|---|
shenzebang/federated-learning-pytorch | A PyTorch-based framework for Federated Learning experiments | 40 |
kenziyuliu/private-cross-silo-fl | This repository provides an implementation of a cross-silo federated learning framework with differential privacy mechanisms. | 25 |
enosair/federated-fdp | A framework for private federated learning that provides differential privacy guarantees at the individual record level. | 7 |
haozzh/fedcr | Evaluates various methods for federated learning on different models and tasks. | 17 |
jeremy313/soteria | An implementation of a defense against model inversion attacks in federated learning | 55 |
charliedinh/pfedme | An implementation of Personalized Federated Learning with Moreau Envelopes and related algorithms using PyTorch for research and experimentation. | 289 |
xiyuanyang45/dynamicpfl | A method for personalizing machine learning models in federated learning settings with adaptive differential privacy to improve performance and robustness | 51 |
galaxylearning/gfl | A decentralized federated learning framework based on blockchain and PyTorch. | 242 |
sap-samples/machine-learning-diff-private-federated-learning | Simulates a federated learning setting to preserve individual data privacy | 360 |
hongyouc/fed-rod | Develops a framework to balance competing goals in federated learning by decoupling generic and personalized prediction tasks. | 14 |
zlz0414/feddar | A framework for federated representation learning with domain awareness in multi-model scenarios. | 2 |
xtra-computing/fedsim | A framework that enables federated learning across multiple datasets while optimizing model performance with record similarities. | 24 |
maxencenoble/differential-privacy-for-heterogeneous-federated-learning | An algorithm for balancing utility and privacy in federated learning on heterogeneous data | 59 |
deu30303/feddefender | A PyTorch implementation of an attack-tolerant federated learning system to train robust local models against malicious attacks from adversaries. | 9 |
securefederatedai/openfl | A framework for enabling collaboration on machine learning projects without sharing sensitive data | 728 |