Time to Focus: A Comprehensive Benchmark Using Time Series Attribution
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Time to Focus: A Comprehensive Benchmark Using Time Series Attribution Methods

8 February 2022

Dominique Mercier

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Papers citing "Time to Focus: A Comprehensive Benchmark Using Time Series Attribution Methods"

18 / 18 papers shown

Title
Class-Dependent Perturbation Effects in Evaluating Time Series Attributions Gregor Baer Isel Grau Chao Zhang Pieter Van Gorp AAML 100 1 0 24 Feb 2025
Robust Explainability: A Tutorial on Gradient-Based Attribution Methods for Deep Neural Networks Ian E. Nielsen Dimah Dera Ghulam Rasool N. Bouaynaya R. Ramachandran FAtt 71 82 0 23 Jul 2021
How to choose an Explainability Method? Towards a Methodical Implementation of XAI in Practice T. Vermeire Thibault Laugel X. Renard David Martens Marcin Detyniecki 35 16 0 09 Jul 2021
Explaining Time Series Predictions with Dynamic Masks Jonathan Crabbé M. Schaar FAtt AI4TS 93 81 0 09 Jun 2021
Sampling Permutations for Shapley Value Estimation Rory Mitchell Joshua N. Cooper E. Frank G. Holmes 62 120 0 25 Apr 2021
Impact of Legal Requirements on Explainability in Machine Learning Adrien Bibal Michael Lognoul A. D. Streel Benoit Frénay ELM AILaw FaML 51 9 0 10 Jul 2020
Opportunities and Challenges in Explainable Artificial Intelligence (XAI): A Survey Arun Das P. Rad XAI 169 604 0 16 Jun 2020
On the (In)fidelity and Sensitivity for Explanations Chih-Kuan Yeh Cheng-Yu Hsieh A. Suggala David I. Inouye Pradeep Ravikumar FAtt 94 455 0 27 Jan 2019
Sanity Checks for Saliency Maps Julius Adebayo Justin Gilmer M. Muelly Ian Goodfellow Moritz Hardt Been Kim FAtt AAML XAI 152 1,972 0 08 Oct 2018
TSViz: Demystification of Deep Learning Models for Time-Series Analysis Shoaib Ahmed Siddiqui Dominique Mercier Mohsin Munir Andreas Dengel Sheraz Ahmed FAtt AI4TS 100 84 0 08 Feb 2018
Visual Interpretability for Deep Learning: a Survey Quanshi Zhang Song-Chun Zhu FaML HAI 146 822 0 02 Feb 2018
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.1K 22,090 0 22 May 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 193 6,027 0 04 Mar 2017
Not Just a Black Box: Learning Important Features Through Propagating Activation Differences Avanti Shrikumar Peyton Greenside A. Shcherbina A. Kundaje FAtt 94 791 0 05 May 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.2K 17,071 0 16 Feb 2016
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 254 4,683 0 21 Dec 2014
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 605 15,907 0 12 Nov 2013