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UQ-ARMED: Uncertainty quantification of adversarially-regularized mixed
  effects deep learning for clustered non-iid data

UQ-ARMED: Uncertainty quantification of adversarially-regularized mixed effects deep learning for clustered non-iid data

29 November 2022
A. Treacher
K. Nguyen
Dylan A. Owens
D. Heitjan
A. Montillo
    FedML
ArXivPDFHTML

Papers citing "UQ-ARMED: Uncertainty quantification of adversarially-regularized mixed effects deep learning for clustered non-iid data"

1 / 1 papers shown
Title
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
287
9,156
0
06 Jun 2015
1