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Significance Tests for Neural Networks

Significance Tests for Neural Networks

16 February 2019
Enguerrand Horel
K. Giesecke
ArXivPDFHTML

Papers citing "Significance Tests for Neural Networks"

7 / 7 papers shown
Title
Complexity, Statistical Risk, and Metric Entropy of Deep Nets Using
  Total Path Variation
Complexity, Statistical Risk, and Metric Entropy of Deep Nets Using Total Path Variation
Andrew R. Barron
Jason M. Klusowski
78
30
0
02 Feb 2019
Universal features of price formation in financial markets: perspectives
  from Deep Learning
Universal features of price formation in financial markets: perspectives from Deep Learning
Justin A. Sirignano
R. Cont
AIFin
59
259
0
19 Mar 2018
A Survey Of Methods For Explaining Black Box Models
A Survey Of Methods For Explaining Black Box Models
Riccardo Guidotti
A. Monreale
Salvatore Ruggieri
Franco Turini
D. Pedreschi
F. Giannotti
XAI
120
3,938
0
06 Feb 2018
Learning Important Features Through Propagating Activation Differences
Learning Important Features Through Propagating Activation Differences
Avanti Shrikumar
Peyton Greenside
A. Kundaje
FAtt
182
3,865
0
10 Apr 2017
Axiomatic Attribution for Deep Networks
Axiomatic Attribution for Deep Networks
Mukund Sundararajan
Ankur Taly
Qiqi Yan
OOD
FAtt
175
5,968
0
04 Mar 2017
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAtt
FaML
1.0K
16,931
0
16 Feb 2016
How to Explain Individual Classification Decisions
How to Explain Individual Classification Decisions
D. Baehrens
T. Schroeter
Stefan Harmeling
M. Kawanabe
K. Hansen
K. Müller
FAtt
126
1,102
0
06 Dec 2009
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