Explaining by Removing: A Unified Framework for Model Explanation

21 November 2020

Papers citing "Explaining by Removing: A Unified Framework for Model Explanation"

50 / 150 papers shown

Title
EMaP: Explainable AI with Manifold-based Perturbations Minh Nhat Vu Huy Mai My T. Thai AAML 35 2 0 18 Sep 2022
From Shapley Values to Generalized Additive Models and back Sebastian Bordt U. V. Luxburg FAtt TDI 69 34 0 08 Sep 2022
Incremental Permutation Feature Importance (iPFI): Towards Online Explanations on Data Streams Fabian Fumagalli Maximilian Muschalik Eyke Hüllermeier Barbara Hammer 24 20 0 05 Sep 2022
Diffusion-based Time Series Imputation and Forecasting with Structured State Space Models Juan Miguel Lopez Alcaraz Nils Strodthoff DiffM 28 167 0 19 Aug 2022
Algorithms to estimate Shapley value feature attributions Hugh Chen Ian Covert Scott M. Lundberg Su-In Lee TDI FAtt 23 212 0 15 Jul 2022
SHAP-XRT: The Shapley Value Meets Conditional Independence Testing Jacopo Teneggi Beepul Bharti Yaniv Romano Jeremias Sulam FAtt 20 3 0 14 Jul 2022
BASED-XAI: Breaking Ablation Studies Down for Explainable Artificial Intelligence Isha Hameed Samuel Sharpe Daniel Barcklow Justin Au-yeung Sahil Verma Jocelyn Huang Brian Barr C. B. Bruss 35 14 0 12 Jul 2022
An Additive Instance-Wise Approach to Multi-class Model Interpretation Vy Vo Van Nguyen Trung Le Quan Hung Tran Gholamreza Haffari S. Çamtepe Dinh Q. Phung FAtt 40 5 0 07 Jul 2022
Causality for Inherently Explainable Transformers: CAT-XPLAIN Subash Khanal Benjamin Brodie Xin Xing Ai-Ling Lin Nathan Jacobs 17 4 0 29 Jun 2022
Analyzing Explainer Robustness via Probabilistic Lipschitzness of Prediction Functions Zulqarnain Khan Davin Hill A. Masoomi Joshua Bone Jennifer Dy AAML 36 3 0 24 Jun 2022
OpenXAI: Towards a Transparent Evaluation of Model Explanations Chirag Agarwal Dan Ley Satyapriya Krishna Eshika Saxena Martin Pawelczyk Nari Johnson Isha Puri Marinka Zitnik Himabindu Lakkaraju XAI 26 140 0 22 Jun 2022
The Manifold Hypothesis for Gradient-Based Explanations Sebastian Bordt Uddeshya Upadhyay Zeynep Akata U. V. Luxburg FAtt AAML 18 12 0 15 Jun 2022
Learning to Estimate Shapley Values with Vision Transformers Ian Covert Chanwoo Kim Su-In Lee FAtt 25 34 0 10 Jun 2022
Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post Hoc Explanations Tessa Han Suraj Srinivas Himabindu Lakkaraju FAtt 30 87 0 02 Jun 2022
Order-sensitive Shapley Values for Evaluating Conceptual Soundness of NLP Models Kaiji Lu Anupam Datta 13 0 0 01 Jun 2022
A Sea of Words: An In-Depth Analysis of Anchors for Text Data Gianluigi Lopardo F. Precioso Damien Garreau 19 6 0 27 May 2022
Explaining Preferences with Shapley Values Robert Hu Siu Lun Chau Jaime Ferrando Huertas Dino Sejdinovic TDI FAtt 11 6 0 26 May 2022
Fairness via Explanation Quality: Evaluating Disparities in the Quality of Post hoc Explanations Jessica Dai Sohini Upadhyay Ulrich Aivodji Stephen H. Bach Himabindu Lakkaraju 37 56 0 15 May 2022
Data Debugging with Shapley Importance over End-to-End Machine Learning Pipelines Bojan Karlavs David Dao Matteo Interlandi Bo-wen Li Sebastian Schelter Wentao Wu Ce Zhang TDI 11 26 0 23 Apr 2022
Ultra-marginal Feature Importance: Learning from Data with Causal Guarantees Joseph Janssen Vincent Guan Elina Robeva 24 7 0 21 Apr 2022
Missingness Bias in Model Debugging Saachi Jain Hadi Salman E. Wong Pengchuan Zhang Vibhav Vineet Sai H. Vemprala A. Madry 22 37 0 19 Apr 2022
From Modern CNNs to Vision Transformers: Assessing the Performance, Robustness, and Classification Strategies of Deep Learning Models in Histopathology Maximilian Springenberg A. Frommholz M. Wenzel Eva Weicken Jackie Ma Nils Strodthoff MedIm 25 42 0 11 Apr 2022
Contrastive language and vision learning of general fashion concepts P. Chia Giuseppe Attanasio Federico Bianchi Silvia Terragni A. Magalhães Diogo Gonçalves C. Greco Jacopo Tagliabue CLIP 15 42 0 08 Apr 2022
Interactive Evolutionary Multi-Objective Optimization via Learning-to-Rank Ke Li Guiyu Lai Xinghu Yao 16 11 0 06 Apr 2022
Don't Get Me Wrong: How to Apply Deep Visual Interpretations to Time Series Christoffer Loeffler Wei-Cheng Lai Bjoern M. Eskofier Dario Zanca Lukas M. Schmidt Christopher Mutschler FAtt AI4TS 33 5 0 14 Mar 2022
Sparse Subspace Clustering for Concept Discovery (SSCCD) Johanna Vielhaben Stefan Blücher Nils Strodthoff 23 6 0 11 Mar 2022
A Consistent and Efficient Evaluation Strategy for Attribution Methods Yao Rong Tobias Leemann V. Borisov Gjergji Kasneci Enkelejda Kasneci FAtt 23 92 0 01 Feb 2022
Post-Hoc Explanations Fail to Achieve their Purpose in Adversarial Contexts Sebastian Bordt Michèle Finck Eric Raidl U. V. Luxburg AILaw 29 77 0 25 Jan 2022
Toward Explainable AI for Regression Models S. Letzgus Patrick Wagner Jonas Lederer Wojciech Samek Klaus-Robert Muller G. Montavon XAI 28 63 0 21 Dec 2021
Using Shapley Values and Variational Autoencoders to Explain Predictive Models with Dependent Mixed Features Lars Henry Berge Olsen I. Glad Martin Jullum K. Aas TDI FAtt 21 17 0 26 Nov 2021
Using Color To Identify Insider Threats Sameer Tajdin Khanna AAML 20 1 0 25 Nov 2021
Beta Shapley: a Unified and Noise-reduced Data Valuation Framework for Machine Learning Yongchan Kwon James Y. Zou TDI 30 122 0 26 Oct 2021
Inferring feature importance with uncertainties in high-dimensional data P. V. Johnsen Inga Strümke S. Riemer-Sørensen A. Dewan M. Langaas TDI FAtt 6 2 0 02 Sep 2021
Temporal Dependencies in Feature Importance for Time Series Predictions Kin Kwan Leung Clayton Rooke Jonathan Smith S. Zuberi M. Volkovs OOD AI4TS 23 24 0 29 Jul 2021
FastSHAP: Real-Time Shapley Value Estimation N. Jethani Mukund Sudarshan Ian Covert Su-In Lee Rajesh Ranganath TDI FAtt 67 122 0 15 Jul 2021
An Imprecise SHAP as a Tool for Explaining the Class Probability Distributions under Limited Training Data Lev V. Utkin A. Konstantinov Kirill Vishniakov FAtt 21 5 0 16 Jun 2021
Accurate Shapley Values for explaining tree-based models Salim I. Amoukou Nicolas Brunel Tangi Salaun TDI FAtt 14 13 0 07 Jun 2021
Energy-Based Learning for Cooperative Games, with Applications to Valuation Problems in Machine Learning Yatao Bian Yu Rong Tingyang Xu Jiaxiang Wu Andreas Krause Junzhou Huang 32 16 0 05 Jun 2021
Do not explain without context: addressing the blind spot of model explanations Katarzyna Wo'znica Katarzyna Pkekala Hubert Baniecki Wojciech Kretowicz El.zbieta Sienkiewicz P. Biecek 23 1 0 28 May 2021
Explaining a Series of Models by Propagating Shapley Values Hugh Chen Scott M. Lundberg Su-In Lee TDI FAtt 22 122 0 30 Apr 2021
Sampling Permutations for Shapley Value Estimation Rory Mitchell Joshua N. Cooper E. Frank G. Holmes 14 113 0 25 Apr 2021
Fast Hierarchical Games for Image Explanations Jacopo Teneggi Alexandre Luster Jeremias Sulam FAtt 31 17 0 13 Apr 2021
Ensembles of Random SHAPs Lev V. Utkin A. Konstantinov FAtt 16 20 0 04 Mar 2021
Have We Learned to Explain?: How Interpretability Methods Can Learn to Encode Predictions in their Interpretations N. Jethani Mukund Sudarshan Yindalon Aphinyanagphongs Rajesh Ranganath FAtt 82 70 0 02 Mar 2021
PredDiff: Explanations and Interactions from Conditional Expectations Stefan Blücher Johanna Vielhaben Nils Strodthoff FAtt 22 19 0 26 Feb 2021
Feature Importance Explanations for Temporal Black-Box Models Akshay Sood M. Craven FAtt OOD 17 15 0 23 Feb 2021
Shapley values for feature selection: The good, the bad, and the axioms D. Fryer Inga Strümke Hien Nguyen FAtt TDI 6 190 0 22 Feb 2021
Improving KernelSHAP: Practical Shapley Value Estimation via Linear Regression Ian Covert Su-In Lee FAtt 10 161 0 02 Dec 2020
Feature Removal Is a Unifying Principle for Model Explanation Methods Ian Covert Scott M. Lundberg Su-In Lee FAtt 31 33 0 06 Nov 2020
From Clustering to Cluster Explanations via Neural Networks Jacob R. Kauffmann Malte Esders Lukas Ruff G. Montavon Wojciech Samek K. Müller 16 68 0 18 Jun 2019