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2103.01890
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Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations
2 March 2021
N. Jethani
Mukund Sudarshan
Yindalon Aphinyanagphongs
Rajesh Ranganath
FAtt
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Papers citing
"Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations"
25 / 25 papers shown
Title
A New Approach to Backtracking Counterfactual Explanations: A Unified Causal Framework for Efficient Model Interpretability
Pouria Fatemi
Ehsan Sharifian
Mohammad Hossein Yassaee
54
0
0
05 May 2025
FW-Shapley: Real-time Estimation of Weighted Shapley Values
Pranoy Panda
Siddharth Tandon
V. Balasubramanian
TDI
83
0
0
09 Mar 2025
On the Challenges and Opportunities in Generative AI
Laura Manduchi
Kushagra Pandey
Robert Bamler
Ryan Cotterell
Sina Daubener
...
F. Wenzel
Frank Wood
Stephan Mandt
Vincent Fortuin
Vincent Fortuin
116
18
0
28 Feb 2024
CXPlain: Causal Explanations for Model Interpretation under Uncertainty
Patrick Schwab
W. Karlen
FAtt
CML
91
208
0
27 Oct 2019
Sanity Checks for Saliency Maps
Julius Adebayo
Justin Gilmer
M. Muelly
Ian Goodfellow
Moritz Hardt
Been Kim
FAtt
AAML
XAI
102
1,947
0
08 Oct 2018
Confounding variables can degrade generalization performance of radiological deep learning models
J. Zech
Marcus A. Badgeley
Manway Liu
A. Costa
J. Titano
Eric K. Oermann
OOD
37
1,165
0
02 Jul 2018
A Benchmark for Interpretability Methods in Deep Neural Networks
Sara Hooker
D. Erhan
Pieter-Jan Kindermans
Been Kim
FAtt
UQCV
60
673
0
28 Jun 2018
Learning to Explain: An Information-Theoretic Perspective on Model Interpretation
Jianbo Chen
Le Song
Martin J. Wainwright
Michael I. Jordan
MLT
FAtt
118
568
0
21 Feb 2018
Interpretable & Explorable Approximations of Black Box Models
Himabindu Lakkaraju
Ece Kamar
R. Caruana
J. Leskovec
FAtt
25
254
0
04 Jul 2017
A Unified Approach to Interpreting Model Predictions
Scott M. Lundberg
Su-In Lee
FAtt
330
21,459
0
22 May 2017
Real Time Image Saliency for Black Box Classifiers
P. Dabkowski
Y. Gal
33
586
0
22 May 2017
ChestX-ray8: Hospital-scale Chest X-ray Database and Benchmarks on Weakly-Supervised Classification and Localization of Common Thorax Diseases
Xiaosong Wang
Yifan Peng
Le Lu
Zhiyong Lu
M. Bagheri
Ronald M. Summers
LM&MA
119
2,495
0
05 May 2017
Learning Important Features Through Propagating Activation Differences
Avanti Shrikumar
Peyton Greenside
A. Kundaje
FAtt
78
3,848
0
10 Apr 2017
REBAR: Low-variance, unbiased gradient estimates for discrete latent variable models
George Tucker
A. Mnih
Chris J. Maddison
John Lawson
Jascha Narain Sohl-Dickstein
BDL
152
282
0
21 Mar 2017
Visualizing Deep Neural Network Decisions: Prediction Difference Analysis
L. Zintgraf
Taco S. Cohen
T. Adel
Max Welling
FAtt
93
707
0
15 Feb 2017
Categorical Reparameterization with Gumbel-Softmax
Eric Jang
S. Gu
Ben Poole
BDL
195
5,323
0
03 Nov 2016
The Concrete Distribution: A Continuous Relaxation of Discrete Random Variables
Chris J. Maddison
A. Mnih
Yee Whye Teh
BDL
84
2,518
0
02 Nov 2016
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
Ramprasaath R. Selvaraju
Michael Cogswell
Abhishek Das
Ramakrishna Vedantam
Devi Parikh
Dhruv Batra
FAtt
179
19,796
0
07 Oct 2016
The Mythos of Model Interpretability
Zachary Chase Lipton
FaML
84
3,672
0
10 Jun 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier
Marco Tulio Ribeiro
Sameer Singh
Carlos Guestrin
FAtt
FaML
392
16,765
0
16 Feb 2016
Evaluating the visualization of what a Deep Neural Network has learned
Wojciech Samek
Alexander Binder
G. Montavon
Sebastian Lapuschkin
K. Müller
XAI
89
1,189
0
21 Sep 2015
Striving for Simplicity: The All Convolutional Net
Jost Tobias Springenberg
Alexey Dosovitskiy
Thomas Brox
Martin Riedmiller
FAtt
137
4,653
0
21 Dec 2014
Auto-Encoding Variational Bayes
Diederik P. Kingma
Max Welling
BDL
321
16,972
0
20 Dec 2013
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
Karen Simonyan
Andrea Vedaldi
Andrew Zisserman
FAtt
112
7,252
0
20 Dec 2013
Visualizing and Understanding Convolutional Networks
Matthew D. Zeiler
Rob Fergus
FAtt
SSL
189
15,825
0
12 Nov 2013
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