DLIME: A Deterministic Local Interpretable Model-Agnostic Explanations Approach for Computer-Aided Diagnosis Systems

24 June 2019

Papers citing "DLIME: A Deterministic Local Interpretable Model-Agnostic Explanations Approach for Computer-Aided Diagnosis Systems"

20 / 20 papers shown

Title
ExplainReduce: Summarising local explanations via proxies Lauri Seppäläinen Mudong Guo Kai Puolamäki FAtt 68 0 0 17 Feb 2025
Feature Responsiveness Scores: Model-Agnostic Explanations for Recourse Seung Hyun Cheon Anneke Wernerfelt Sorelle A. Friedler Berk Ustun FaML FAtt 124 1 0 29 Oct 2024
BELLA: Black box model Explanations by Local Linear Approximations N. Radulovic Albert Bifet Fabian M. Suchanek FAtt 81 1 0 18 May 2023
SurvLIME: A method for explaining machine learning survival models M. Kovalev Lev V. Utkin E. Kasimov 167 90 0 18 Mar 2020
Do Not Trust Additive Explanations Alicja Gosiewska P. Biecek 25 41 0 27 Mar 2019
On The Stability of Interpretable Models Riccardo Guidotti Salvatore Ruggieri FAtt 27 10 0 22 Oct 2018
Model Agnostic Supervised Local Explanations Gregory Plumb Denali Molitor Ameet Talwalkar FAtt LRM MILM 87 196 0 09 Jul 2018
Locally Interpretable Models and Effects based on Supervised Partitioning (LIME-SUP) Linwei Hu Jie Chen V. Nair Agus Sudjianto FAtt 29 63 0 02 Jun 2018
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 495 21,613 0 22 May 2017
Real Time Image Saliency for Black Box Classifiers P. Dabkowski Y. Gal 42 586 0 22 May 2017
Interpretable Explanations of Black Boxes by Meaningful Perturbation Ruth C. Fong Andrea Vedaldi FAtt AAML 48 1,514 0 11 Apr 2017
Right for the Right Reasons: Training Differentiable Models by Constraining their Explanations A. Ross M. C. Hughes Finale Doshi-Velez FAtt 103 585 0 10 Mar 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 110 5,920 0 04 Mar 2017
Distribution-Free Predictive Inference For Regression Jing Lei M. G'Sell Alessandro Rinaldo Robert Tibshirani Larry A. Wasserman 190 832 0 14 Apr 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 551 16,828 0 16 Feb 2016
Learning Deep Features for Discriminative Localization Bolei Zhou A. Khosla Àgata Lapedriza A. Oliva Antonio Torralba SSL SSeg FAtt 159 9,266 0 14 Dec 2015
A Random Forest Guided Tour Gérard Biau Erwan Scornet AI4TS 170 2,784 0 18 Nov 2015
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 162 7,252 0 20 Dec 2013
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 310 15,825 0 12 Nov 2013
How to Explain Individual Classification Decisions D. Baehrens T. Schroeter Stefan Harmeling M. Kawanabe K. Hansen K. Müller FAtt 101 1,098 0 06 Dec 2009