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Saliency methods are a popular approach for model debugging and explainability.
Visualizing higher-layer features of a deep network
Dumitru Erhan, Yoshua Bengio, Aaron Courville, and Pascal Vincent · 2009
Earlier work this paper cites.
On random weights and unsupervised feature learning
Andrew M Saxe, Pang Wei Koh, Zhenghao Chen, Maneesh Bhand, Bipin Suresh, and Andrew Y Ng · 2011
Earlier work this paper cites.
Deep inside convolutional networks: Visualising image classification models and saliency maps
Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman · 2013
Earlier work this paper cites.
Striving for simplicity: The all convolutional net
Jost Tobias Springenberg, Alexey Dosovitskiy, Thomas Brox, and Martin Riedmiller · 2014
Earlier work this paper cites.
Causal inference in statistics: A primer
Judea Pearl, Madelyn Glymour, and Nicholas P Jewell · 2016
Earlier work this paper cites.
Evaluating the visualization of what a deep neural network has learned
Wojciech Samek, Alexander Binder, Grégoire Montavon, Sebastian Lapuschkin, and Klaus-Robert Müller · 2016
Earlier work this paper cites.
Real time image saliency for black box classifiers
Piotr Dabkowski and Yarin Gal · 2017
Earlier work this paper cites.
Smoothgrad: removing noise by adding noise
Daniel Smilkov, Nikhil Thorat, Been Kim, Fernanda Viégas, and Martin Wattenberg · 2017
Cited alongside, same era.
Axiomatic attribution for deep networks
Mukund Sundararajan, Ankur Taly, and Qiqi Yan · 2017
Cited alongside, same era.
Sanity checks for saliency maps
Julius Adebayo, Justin Gilmer, Michael Muelly, Ian Goodfellow, Moritz Hardt, and Been Kim · 2018
Cited alongside, same era.
Methods for interpreting and understanding deep neural networks
Grégoire Montavon, Wojciech Samek, and Klaus-Robert Müller · 2018
Cited alongside, same era.
Deep image prior
Dmitry Ulyanov, Andrea Vedaldi, and Victor Lempitsky · 2018
Cited alongside, same era.
Ground truth evaluation of neural network explanations with clevr-xai
Leila Arras, Ahmed Osman, and Wojciech Samek · 2020
Later among the works it cites.
Assessing the validity of saliency maps for abnormality localization in medical imaging
Nishanth Thumbavanam Arun, Nathan Gaw, Praveer Singh, Ken Chang, Katharina Viktoria Hoebel, Jay Patel, Mishka Gidwani, and Jayashree Kalpathy-Cramer · 2020
Later among the works it cites.
Thomas Fel, David Vigouroux, Rémi Cadène, and Thomas Serre · 2020
Later among the works it cites.
Sanity checks for saliency metrics
Richard Tomsett, Dan Harborne, Supriyo Chakraborty, Prudhvi Gurram, and Alun Preece · 2020
Later among the works it cites.
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Julius Adebayo, Michael Muelly, Ilaria Liccardi, and Been Kim · 2020
Cited alongside, same era.
Shuoyang Ding and Philipp Koehn · 2021
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Do feature attribution methods correctly attribute features?
Yilun Zhou, Serena Booth, Marco Tulio Ribeiro, and Julie Shah · 2021
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