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Testing the robustness of attribution methods for convolutional neural
  networks in MRI-based Alzheimer's disease classification

Testing the robustness of attribution methods for convolutional neural networks in MRI-based Alzheimer's disease classification

19 September 2019
Fabian Eitel
K. Ritter
    OOD
    FAtt
ArXivPDFHTML

Papers citing "Testing the robustness of attribution methods for convolutional neural networks in MRI-based Alzheimer's disease classification"

12 / 12 papers shown
Title
Uncovering convolutional neural network decisions for diagnosing
  multiple sclerosis on conventional MRI using layer-wise relevance propagation
Uncovering convolutional neural network decisions for diagnosing multiple sclerosis on conventional MRI using layer-wise relevance propagation
Fabian Eitel
Emily Soehler
J. Bellmann-Strobl
A. Brandt
K. Ruprecht
...
M. Weygandt
J. Haynes
M. Scheel
Friedemann Paul
K. Ritter
46
132
0
18 Apr 2019
Sanity Checks for Saliency Maps
Sanity Checks for Saliency Maps
Julius Adebayo
Justin Gilmer
M. Muelly
Ian Goodfellow
Moritz Hardt
Been Kim
FAtt
AAML
XAI
123
1,965
0
08 Oct 2018
End-To-End Alzheimer's Disease Diagnosis and Biomarker Identification
End-To-End Alzheimer's Disease Diagnosis and Biomarker Identification
S. Esmaeilzadeh
D. Belivanis
K. Pohl
Ehsan Adeli
MedIm
39
96
0
01 Oct 2018
Visualizing Convolutional Networks for MRI-based Diagnosis of
  Alzheimer's Disease
Visualizing Convolutional Networks for MRI-based Diagnosis of Alzheimer's Disease
J. Rieke
Fabian Eitel
M. Weygandt
J. Haynes
K. Ritter
FAtt
47
86
0
08 Aug 2018
On the Robustness of Interpretability Methods
On the Robustness of Interpretability Methods
David Alvarez-Melis
Tommi Jaakkola
76
526
0
21 Jun 2018
Methods for Interpreting and Understanding Deep Neural Networks
Methods for Interpreting and Understanding Deep Neural Networks
G. Montavon
Wojciech Samek
K. Müller
FaML
278
2,262
0
24 Jun 2017
Learning Important Features Through Propagating Activation Differences
Learning Important Features Through Propagating Activation Differences
Avanti Shrikumar
Peyton Greenside
A. Kundaje
FAtt
188
3,869
0
10 Apr 2017
Axiomatic Attribution for Deep Networks
Axiomatic Attribution for Deep Networks
Mukund Sundararajan
Ankur Taly
Qiqi Yan
OOD
FAtt
175
5,986
0
04 Mar 2017
Residual and Plain Convolutional Neural Networks for 3D Brain MRI
  Classification
Residual and Plain Convolutional Neural Networks for 3D Brain MRI Classification
Sergey Korolev
Amir Safiullin
Mikhail Belyaev
Yulia Dodonova
MedIm
36
367
0
23 Jan 2017
Striving for Simplicity: The All Convolutional Net
Striving for Simplicity: The All Convolutional Net
Jost Tobias Springenberg
Alexey Dosovitskiy
Thomas Brox
Martin Riedmiller
FAtt
240
4,667
0
21 Dec 2014
Deep Inside Convolutional Networks: Visualising Image Classification
  Models and Saliency Maps
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
Karen Simonyan
Andrea Vedaldi
Andrew Zisserman
FAtt
301
7,289
0
20 Dec 2013
Visualizing and Understanding Convolutional Networks
Visualizing and Understanding Convolutional Networks
Matthew D. Zeiler
Rob Fergus
FAtt
SSL
563
15,874
0
12 Nov 2013
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