Saliency strikes back: How filtering out high frequencies improves
white-box explanations

Saliency strikes back: How filtering out high frequencies improves white-box explanations

18 July 2023

Sabine Muzellec

Papers citing "Saliency strikes back: How filtering out high frequencies improves white-box explanations"

18 / 18 papers shown

Title
Learning with Explanation Constraints Rattana Pukdee Dylan Sam J. Zico Kolter Maria-Florina Balcan Pradeep Ravikumar FAtt 52 6 0 25 Mar 2023
On the coalitional decomposition of parameters of interest Marouane Il Idrissi Nicolas Bousquet Fabrice Gamboa Bertrand Iooss Jean-Michel Loubes 24 8 0 06 Jan 2023
Making Sense of Dependence: Efficient Black-box Explanations Using Dependence Measure Paul Novello Thomas Fel David Vigouroux FAtt 37 28 0 13 Jun 2022
Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post Hoc Explanations Tessa Han Suraj Srinivas Himabindu Lakkaraju FAtt 52 86 0 02 Jun 2022
Rethinking Stability for Attribution-based Explanations Chirag Agarwal Nari Johnson Martin Pawelczyk Satyapriya Krishna Eshika Saxena Marinka Zitnik Himabindu Lakkaraju FAtt 49 50 0 14 Mar 2022
Formalizing Trust in Artificial Intelligence: Prerequisites, Causes and Goals of Human Trust in AI Alon Jacovi Ana Marasović Tim Miller Yoav Goldberg 281 436 0 15 Oct 2020
Reliable Post hoc Explanations: Modeling Uncertainty in Explainability Dylan Slack Sophie Hilgard Sameer Singh Himabindu Lakkaraju FAtt 40 162 0 11 Aug 2020
Evaluating and Aggregating Feature-based Model Explanations Umang Bhatt Adrian Weller J. M. F. Moura XAI 70 219 0 01 May 2020
RISE: Randomized Input Sampling for Explanation of Black-box Models Vitali Petsiuk Abir Das Kate Saenko FAtt 97 1,159 0 19 Jun 2018
Noise-adding Methods of Saliency Map as Series of Higher Order Partial Derivative Junghoon Seo J. Choe Jamyoung Koo Seunghyeon Jeon Beomsu Kim Taegyun Jeon FAtt ODL 16 29 0 08 Jun 2018
Interpretable Explanations of Black Boxes by Meaningful Perturbation Ruth C. Fong Andrea Vedaldi FAtt AAML 30 1,514 0 11 Apr 2017
Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Kundaje FAtt 82 3,848 0 10 Apr 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 70 5,920 0 04 Mar 2017
The Shattered Gradients Problem: If resnets are the answer, then what is the question? David Balduzzi Marcus Frean Lennox Leary J. P. Lewis Kurt Wan-Duo Ma Brian McWilliams ODL 46 399 0 28 Feb 2017
Identity Mappings in Deep Residual Networks Kaiming He Xinming Zhang Shaoqing Ren Jian Sun 262 10,149 0 16 Mar 2016
Learning Deep Features for Discriminative Localization Bolei Zhou A. Khosla Àgata Lapedriza A. Oliva Antonio Torralba SSL SSeg FAtt 119 9,266 0 14 Dec 2015
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 144 4,653 0 21 Dec 2014
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 208 15,825 0 12 Nov 2013