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An Uncertainty-Aware, Shareable and Transparent Neural Network
  Architecture for Brain-Age Modeling

An Uncertainty-Aware, Shareable and Transparent Neural Network Architecture for Brain-Age Modeling

16 July 2021
Tim Hahn
J. Ernsting
N. Winter
V. Holstein
Ramona Leenings
Marie Beisemann
L. Fisch
K. Sarink
D. Emden
N. Opel
R. Redlich
J. Repple
D. Grotegerd
S. Meinert
J. Hirsch
Thoralf Niendorf
B. Endemann
F. Bamberg
Thomas Kroncke
Robin Bülow
H. Völzke
O. Stackelberg
R. Sowade
L. Umutlu
B. Schmidt
S. Caspers
German National Cohort Study Center Consortium
H. Kugel
T. Kircher
Benjamin Risse
Christian Gaser
James H. Cole
U. Dannlowski
Klaus Berger
    OOD
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Papers citing "An Uncertainty-Aware, Shareable and Transparent Neural Network Architecture for Brain-Age Modeling"

2 / 2 papers shown
Title
Predicting brain-age from raw T 1 -weighted Magnetic Resonance Imaging
  data using 3D Convolutional Neural Networks
Predicting brain-age from raw T 1 -weighted Magnetic Resonance Imaging data using 3D Convolutional Neural Networks
L. Fisch
J. Ernsting
N. Winter
V. Holstein
Ramona Leenings
...
T. Kircher
Benjamin Risse
U. Dannlowski
Klaus Berger
Tim Hahn
MedIm
35
12
0
22 Mar 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
287
9,167
0
06 Jun 2015
1