A-Bayesian-Federated-Learning-Framework-with-Online-Laplace-Approximation

Bayesian federated learning framework

A framework for collaborative machine learning across distributed datasets using Bayesian methods and online approximation techniques

GitHub

8 stars
5 watching
4 forks
Language: Python
last commit: over 3 years ago

Related projects:

Repository Description Stars
ignavierng/notears-admm An implementation of Bayesian network structure learning with continuous optimization for federated learning. 10
xtra-computing/fedov Develops a framework to address label skews in one-shot federated learning by partitioning data and adapting models. 14
smilelab-fl/fedlab A flexible framework for distributed machine learning where participants train local models and collaboratively optimize them without sharing data 738
litian96/ditto A framework for personalized federated learning to balance fairness and robustness in decentralized machine learning systems. 137
aiot-mlsys-lab/fedrolex An approach to heterogeneous federated learning allowing for model training on diverse devices with varying resources. 61
ibm/federated-learning-lib A framework for collaborative distributed machine learning in enterprise environments. 499
kai-yue/ntk-fed A framework for federated learning that leverages the neural tangent kernel to address statistical heterogeneity in distributed machine learning. 3
raymin0223/logo An implementation of federated active learning with a novel sampling strategy to improve performance on decentralized machine learning tasks 31
omarfoq/fedem Develops and evaluates federated learning algorithms for personalizing machine learning models across heterogeneous client data distributions. 154
mediabrain-sjtu/pfedgraph This project enables personalized federated learning with inferred collaboration graphs to improve the performance of machine learning models on non-IID (non-independent and identically distributed) datasets. 26
yamingguo98/fediir An implementation of a federated learning algorithm that generalizes to out-of-distribution scenarios using implicit invariant relationships 9
allenbeau/pfedbayes An implementation of personalized federated learning using variational Bayesian inference on the MNIST dataset 49
hypervoyager/pfl An implementation of heterogeneous federated learning with parallel edge and server computation 16
xtra-computing/fedsim A framework that enables federated learning across multiple datasets while optimizing model performance with record similarities. 24
bytedance/feddecorr Provides an implementation of various heterogeneous federated learning methods and datasets to mitigate dimensional collapse in distributed machine learning 63