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Federated Bayesian Deep Learning: The Application of Statistical
  Aggregation Methods to Bayesian Models

Federated Bayesian Deep Learning: The Application of Statistical Aggregation Methods to Bayesian Models

22 March 2024
John Fischer
Marko Orescanin
Justin Loomis
Patrick McClure
    FedML
ArXivPDFHTML

Papers citing "Federated Bayesian Deep Learning: The Application of Statistical Aggregation Methods to Bayesian Models"

3 / 3 papers shown
Title
Federated Learning on Non-IID Data Silos: An Experimental Study
Federated Learning on Non-IID Data Silos: An Experimental Study
Q. Li
Yiqun Diao
Quan Chen
Bingsheng He
FedML
OOD
87
946
0
03 Feb 2021
A Bayesian Federated Learning Framework with Online Laplace
  Approximation
A Bayesian Federated Learning Framework with Online Laplace Approximation
Liang Liu
Xi Jiang
Feng Zheng
Hong Chen
Guo-Jun Qi
Heng-Chiao Huang
Ling Shao
FedML
43
53
0
03 Feb 2021
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,136
0
06 Jun 2015
1