Aggregating explanation methods for stable and robust explainability

Aggregating explanation methods for stable and robust explainability

1 March 2019

Lars Kai Hansen

Papers citing "Aggregating explanation methods for stable and robust explainability"

15 / 15 papers shown

Title
Explanations can be manipulated and geometry is to blame Ann-Kathrin Dombrowski Maximilian Alber Christopher J. Anders M. Ackermann K. Müller Pan Kessel AAML FAtt 81 331 0 19 Jun 2019
Fooling Neural Network Interpretations via Adversarial Model Manipulation Juyeon Heo Sunghwan Joo Taesup Moon AAML FAtt 93 203 0 06 Feb 2019
Fairwashing: the risk of rationalization Ulrich Aïvodji Hiromi Arai O. Fortineau Sébastien Gambs Satoshi Hara Alain Tapp FaML 47 147 0 28 Jan 2019
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV) Been Kim Martin Wattenberg Justin Gilmer Carrie J. Cai James Wexler F. Viégas Rory Sayres FAtt 211 1,838 0 30 Nov 2017
The (Un)reliability of saliency methods Pieter-Jan Kindermans Sara Hooker Julius Adebayo Maximilian Alber Kristof T. Schütt Sven Dähne D. Erhan Been Kim FAtt XAI 91 685 0 02 Nov 2017
Interpretable Convolutional Neural Networks Quanshi Zhang Ying Nian Wu Song-Chun Zhu FAtt 64 780 0 02 Oct 2017
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 273 8,876 0 25 Aug 2017
Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Kundaje FAtt 192 3,869 0 10 Apr 2017
What Uncertainties Do We Need in Bayesian Deep Learning for Computer Vision? Alex Kendall Y. Gal BDL OOD UD UQCV PER 352 4,704 0 15 Mar 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 175 5,986 0 04 Mar 2017
Learning Deep Features for Discriminative Localization Bolei Zhou A. Khosla Àgata Lapedriza A. Oliva Antonio Torralba SSL SSeg FAtt 247 9,308 0 14 Dec 2015
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 244 4,667 0 21 Dec 2014
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 305 7,289 0 20 Dec 2013
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 587 15,876 0 12 Nov 2013
ADADELTA: An Adaptive Learning Rate Method Matthew D. Zeiler ODL 141 6,626 0 22 Dec 2012

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