REVEL Framework to measure Local Linear Explanations for black-box models: Deep Learning Image Classification case of study

11 November 2022

Papers citing "REVEL Framework to measure Local Linear Explanations for black-box models: Deep Learning Image Classification case of study"

7 / 7 papers shown

Title
To trust or not to trust an explanation: using LEAF to evaluate local linear XAI methods E. Amparore Alan Perotti P. Bajardi FAtt 69 67 0 01 Jun 2021
Reliable Post hoc Explanations: Modeling Uncertainty in Explainability Dylan Slack Sophie Hilgard Sameer Singh Himabindu Lakkaraju FAtt 106 162 0 11 Aug 2020
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI Alejandro Barredo Arrieta Natalia Díaz Rodríguez Javier Del Ser Adrien Bennetot Siham Tabik ... S. Gil-Lopez Daniel Molina Richard Benjamins Raja Chatila Francisco Herrera XAI 135 6,321 0 22 Oct 2019
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks Mingxing Tan Quoc V. Le 3DV MedIm 172 18,224 0 28 May 2019
A Survey Of Methods For Explaining Black Box Models Riccardo Guidotti A. Monreale Salvatore Ruggieri Franco Turini D. Pedreschi F. Giannotti XAI 150 3,989 0 06 Feb 2018
Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms Han Xiao Kashif Rasul Roland Vollgraf 285 8,928 0 25 Aug 2017
"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