Explaining image classifiers by removing input features using generative models

9 October 2019

Papers citing "Explaining image classifiers by removing input features using generative models"

5 / 5 papers shown

Title
Deconfounding to Explanation Evaluation in Graph Neural Networks Yingmin Wu Xiang Wang An Zhang Helen Zhou Fuli Feng Xiangnan He Tat-Seng Chua FAtt CML 87 14 0 21 Jan 2022
Generative Counterfactuals for Neural Networks via Attribute-Informed Perturbation Fan Yang Ninghao Liu Mengnan Du X. Hu OOD 53 17 0 18 Jan 2021
Shapley explainability on the data manifold Christopher Frye Damien de Mijolla T. Begley Laurence Cowton Megan Stanley Ilya Feige FAtt TDI 73 102 0 01 Jun 2020
Explaining Deep Neural Networks and Beyond: A Review of Methods and Applications Wojciech Samek G. Montavon Sebastian Lapuschkin Christopher J. Anders K. Müller XAI 134 83 0 17 Mar 2020
Deep Radar Waveform Design for Efficient Automotive Radar Sensing Shahin Khobahi Arindam Bose M. Soltanalian 42 18 0 17 Dec 2019