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1910.12336
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CXPlain: Causal Explanations for Model Interpretation under Uncertainty
27 October 2019
Patrick Schwab
W. Karlen
FAtt
CML
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Papers citing
"CXPlain: Causal Explanations for Model Interpretation under Uncertainty"
8 / 108 papers shown
Title
Adversarial Infidelity Learning for Model Interpretation
Jian Liang
Bing Bai
Yuren Cao
Kun Bai
Fei Wang
AAML
103
18
0
09 Jun 2020
Clinical Predictive Models for COVID-19: Systematic Study
Patrick Schwab
August DuMont Schütte
Benedikt Dietz
Stefan Bauer
OOD
ELM
88
35
0
17 May 2020
An interpretable neural network model through piecewise linear approximation
Mengzhuo Guo
Qingpeng Zhang
Xiuwu Liao
D. Zeng
MILM
FAtt
51
8
0
20 Jan 2020
A Deep Learning Approach to Diagnosing Multiple Sclerosis from Smartphone Data
Patrick Schwab
W. Karlen
68
26
0
02 Jan 2020
Contextual Prediction Difference Analysis for Explaining Individual Image Classifications
Jindong Gu
Volker Tresp
FAtt
51
8
0
21 Oct 2019
Learning Decision Trees Recurrently Through Communication
Stephan Alaniz
Diego Marcos
Bernt Schiele
Zeynep Akata
58
16
0
05 Feb 2019
Learning Counterfactual Representations for Estimating Individual Dose-Response Curves
Patrick Schwab
Lorenz Linhardt
Stefan Bauer
J. M. Buhmann
W. Karlen
CML
OOD
101
135
0
03 Feb 2019
MARGIN: Uncovering Deep Neural Networks using Graph Signal Analysis
Rushil Anirudh
Jayaraman J. Thiagarajan
R. Sridhar
T. Bremer
FAtt
AAML
72
12
0
15 Nov 2017
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