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Distributed Weight Consolidation: A Brain Segmentation Case Study

Distributed Weight Consolidation: A Brain Segmentation Case Study

28 May 2018
Patrick McClure
C. Zheng
Jakub R. Kaczmarzyk
John Rogers-Lee
Satrajit S. Ghosh
D. Nielson
P. Bandettini
Francisco Pereira
ArXivPDFHTML

Papers citing "Distributed Weight Consolidation: A Brain Segmentation Case Study"

3 / 3 papers shown
Title
Subspace Regularizers for Few-Shot Class Incremental Learning
Subspace Regularizers for Few-Shot Class Incremental Learning
Afra Feyza Akyürek
Ekin Akyürek
Derry Wijaya
Jacob Andreas
CLL
21
59
0
13 Oct 2021
Knowing what you know in brain segmentation using Bayesian deep neural
  networks
Knowing what you know in brain segmentation using Bayesian deep neural networks
Patrick McClure
Nao Rho
J. Lee
Jakub R. Kaczmarzyk
C. Zheng
Satrajit S. Ghosh
D. Nielson
Adam G. Thomas
P. Bandettini
Francisco Pereira
UQCV
3DV
BDL
24
52
0
03 Dec 2018
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
9,138
0
06 Jun 2015
1