Robustness of Visual Explanations to Common Data Augmentation

18 April 2023

Papers citing "Robustness of Visual Explanations to Common Data Augmentation"

19 / 19 papers shown

Title
Analyzing Effects of Mixed Sample Data Augmentation on Model Interpretability Soyoun Won Sung-Ho Bae Seong Tae Kim 79 2 0 26 Mar 2023
Quantus: An Explainable AI Toolkit for Responsible Evaluation of Neural Network Explanations and Beyond Anna Hedström Leander Weber Dilyara Bareeva Daniel G. Krakowczyk Franz Motzkus Wojciech Samek Sebastian Lapuschkin Marina M.-C. Höhne XAI ELM 74 179 0 14 Feb 2022
Software for Dataset-wide XAI: From Local Explanations to Global Insights with Zennit, CoRelAy, and ViRelAy Christopher J. Anders David Neumann Wojciech Samek K. Müller Sebastian Lapuschkin 89 66 0 24 Jun 2021
EfficientNetV2: Smaller Models and Faster Training Mingxing Tan Quoc V. Le EgoV 137 2,730 0 01 Apr 2021
Captum: A unified and generic model interpretability library for PyTorch Narine Kokhlikyan Vivek Miglani Miguel Martin Edward Wang B. Alsallakh ... Alexander Melnikov Natalia Kliushkina Carlos Araya Siqi Yan Orion Reblitz-Richardson FAtt 159 853 0 16 Sep 2020
IROF: a low resource evaluation metric for explanation methods Laura Rieger Lars Kai Hansen 65 55 0 09 Mar 2020
Towards Best Practice in Explaining Neural Network Decisions with LRP M. Kohlbrenner Alexander Bauer Shinichi Nakajima Alexander Binder Wojciech Samek Sebastian Lapuschkin 93 149 0 22 Oct 2019
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 88 335 0 19 Jun 2019
Sanity Checks for Saliency Maps Julius Adebayo Justin Gilmer M. Muelly Ian Goodfellow Moritz Hardt Been Kim FAtt AAML XAI 159 1,972 0 08 Oct 2018
A Theoretical Explanation for Perplexing Behaviors of Backpropagation-based Visualizations Weili Nie Yang Zhang Ankit B. Patel FAtt 161 151 0 18 May 2018
The Effectiveness of Data Augmentation in Image Classification using Deep Learning Luis Perez Jason Wang 92 2,794 0 13 Dec 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 109 689 0 02 Nov 2017
Random Erasing Data Augmentation Zhun Zhong Liang Zheng Guoliang Kang Shaozi Li Yi Yang 116 3,652 0 16 Aug 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 211 6,027 0 04 Mar 2017
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 255 4,683 0 21 Dec 2014
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 284 19,145 0 20 Dec 2014
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 328 7,321 0 20 Dec 2013
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 609 15,907 0 12 Nov 2013
Deep Big Simple Neural Nets Excel on Handwritten Digit Recognition D. Ciresan U. Meier L. Gambardella Jürgen Schmidhuber 127 994 0 01 Mar 2010