Why model why? Assessing the strengths and limitations of LIME

30 November 2020

Papers citing "Why model why? Assessing the strengths and limitations of LIME"

19 / 19 papers shown

Title
Coherent Local Explanations for Mathematical Optimization Daan Otto Jannis Kurtz S. Ilker Birbil 73 0 0 07 Feb 2025
Enhancing IoT Network Security through Adaptive Curriculum Learning and XAI Sathwik Narkedimilli Sujith Makam Amballa Venkata Sriram Sai Prashanth Mallellu MSVPJ Sathvik Ranga Rao Venkatesha Prasad 66 0 0 20 Jan 2025
A Comparative Analysis of DNN-based White-Box Explainable AI Methods in Network Security Osvaldo Arreche Mustafa Abdallah AAML 137 1 0 14 Jan 2025
Model Agnostic Contrastive Explanations for Structured Data Amit Dhurandhar Tejaswini Pedapati Avinash Balakrishnan Pin-Yu Chen Karthikeyan Shanmugam Ruchi Puri FAtt 56 82 0 31 May 2019
Model-Agnostic Counterfactual Explanations for Consequential Decisions Amir-Hossein Karimi Gilles Barthe Borja Balle Isabel Valera 71 320 0 27 May 2019
CERTIFAI: Counterfactual Explanations for Robustness, Transparency, Interpretability, and Fairness of Artificial Intelligence models Shubham Sharma Jette Henderson Joydeep Ghosh 28 87 0 20 May 2019
Local Interpretable Model-agnostic Explanations of Bayesian Predictive Models via Kullback-Leibler Projections Tomi Peltola FAtt BDL 29 39 0 05 Oct 2018
Visualizing the Feature Importance for Black Box Models Giuseppe Casalicchio Christoph Molnar B. Bischl FAtt 31 182 0 18 Apr 2018
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning Nicolas Papernot Patrick McDaniel OOD AAML 81 505 0 13 Mar 2018
Interpretability via Model Extraction Osbert Bastani Carolyn Kim Hamsa Bastani FAtt 47 129 0 29 Jun 2017
Real Time Image Saliency for Black Box Classifiers P. Dabkowski Y. Gal 40 586 0 22 May 2017
Interpretable Explanations of Black Boxes by Meaningful Perturbation Ruth C. Fong Andrea Vedaldi FAtt AAML 45 1,514 0 11 Apr 2017
Understanding Black-box Predictions via Influence Functions Pang Wei Koh Percy Liang TDI 134 2,854 0 14 Mar 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 108 5,920 0 04 Mar 2017
"What is Relevant in a Text Document?": An Interpretable Machine Learning Approach L. Arras F. Horn G. Montavon K. Müller Wojciech Samek 36 288 0 23 Dec 2016
An unexpected unity among methods for interpreting model predictions Scott M. Lundberg Su-In Lee FAtt 42 110 0 22 Nov 2016
Nothing Else Matters: Model-Agnostic Explanations By Identifying Prediction Invariance Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt 39 64 0 17 Nov 2016
Learning Deep Features for Discriminative Localization Bolei Zhou A. Khosla Àgata Lapedriza A. Oliva Antonio Torralba SSL SSeg FAtt 150 9,266 0 14 Dec 2015
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 258 15,825 0 12 Nov 2013