How to Manipulate CNNs to Make Them Lie: the GradCAM Case

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How to Manipulate CNNs to Make Them Lie: the GradCAM Case

25 July 2019

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Papers citing "How to Manipulate CNNs to Make Them Lie: the GradCAM Case"

16 / 16 papers shown

Title
Sanity Checks for Saliency Maps Julius Adebayo Justin Gilmer M. Muelly Ian Goodfellow Moritz Hardt Been Kim FAtt AAML XAI 152 1,970 0 08 Oct 2018
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 109 688 0 02 Nov 2017
BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain Tianyu Gu Brendan Dolan-Gavitt S. Garg SILM 130 1,782 0 22 Aug 2017
Real Time Image Saliency for Black Box Classifiers P. Dabkowski Y. Gal 72 593 0 22 May 2017
Interpretable Explanations of Black Boxes by Meaningful Perturbation Ruth C. Fong Andrea Vedaldi FAtt AAML 83 1,526 0 11 Apr 2017
Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Kundaje FAtt 203 3,884 0 10 Apr 2017
Understanding Black-box Predictions via Influence Functions Pang Wei Koh Percy Liang TDI 219 2,910 0 14 Mar 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 193 6,027 0 04 Mar 2017
Towards the Science of Security and Privacy in Machine Learning Nicolas Papernot Patrick McDaniel Arunesh Sinha Michael P. Wellman AAML 96 474 0 11 Nov 2016
Learning Deep Features for Discriminative Localization Bolei Zhou A. Khosla Àgata Lapedriza A. Oliva Antonio Torralba SSL SSeg FAtt 253 9,342 0 14 Dec 2015
Object Detectors Emerge in Deep Scene CNNs Bolei Zhou A. Khosla Àgata Lapedriza A. Oliva Antonio Torralba ObjD 164 1,283 0 22 Dec 2014
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 254 4,681 0 21 Dec 2014
CNN Features off-the-shelf: an Astounding Baseline for Recognition A. Razavian Hossein Azizpour Josephine Sullivan S. Carlsson 163 4,945 0 23 Mar 2014
Do Deep Nets Really Need to be Deep? Lei Jimmy Ba R. Caruana 188 2,120 0 21 Dec 2013
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 317 7,321 0 20 Dec 2013
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 603 15,907 0 12 Nov 2013

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