Local Explanation Methods for Deep Neural Networks Lack Sensitivity to Parameter Values

8 October 2018

Justin Gilmer

Papers citing "Local Explanation Methods for Deep Neural Networks Lack Sensitivity to Parameter Values"

26 / 26 papers shown

Title
B-cosification: Transforming Deep Neural Networks to be Inherently Interpretable Shreyash Arya Sukrut Rao Moritz Bohle Bernt Schiele 68 2 0 28 Jan 2025
Flow AM: Generating Point Cloud Global Explanations by Latent Alignment Hanxiao Tan 39 1 0 29 Apr 2024
Occlusion Sensitivity Analysis with Augmentation Subspace Perturbation in Deep Feature Space Pedro Valois Koichiro Niinuma Kazuhiro Fukui AAML 24 4 0 25 Nov 2023
A New Perspective on Evaluation Methods for Explainable Artificial Intelligence (XAI) Timo Speith Markus Langer 29 12 0 26 Jul 2023
SwiFT: Swin 4D fMRI Transformer P. Y. Kim Junbeom Kwon Sunghwan Joo Sang-Peel Bae Donggyu Lee Yoonho Jung Shinjae Yoo Jiook Cha Taesup Moon MedIm 30 20 0 12 Jul 2023
The Generalizability of Explanations Hanxiao Tan FAtt 18 1 0 23 Feb 2023
Opti-CAM: Optimizing saliency maps for interpretability Hanwei Zhang Felipe Torres R. Sicre Yannis Avrithis Stéphane Ayache 33 22 0 17 Jan 2023
On the Robustness of Explanations of Deep Neural Network Models: A Survey Amlan Jyoti Karthik Balaji Ganesh Manoj Gayala Nandita Lakshmi Tunuguntla Sandesh Kamath V. Balasubramanian XAI FAtt AAML 32 4 0 09 Nov 2022
Shap-CAM: Visual Explanations for Convolutional Neural Networks based on Shapley Value Quan Zheng Ziwei Wang Jie Zhou Jiwen Lu FAtt 28 31 0 07 Aug 2022
Reliable Visualization for Deep Speaker Recognition Pengqi Li Lantian Li A. Hamdulla Dong Wang HAI 40 9 0 08 Apr 2022
Metrics for saliency map evaluation of deep learning explanation methods T. Gomez Thomas Fréour Harold Mouchère XAI FAtt 69 41 0 31 Jan 2022
Global explainability in aligned image modalities Justin Engelmann Amos Storkey Miguel O. Bernabeu FAtt 22 4 0 17 Dec 2021
Accelerating Multi-Objective Neural Architecture Search by Random-Weight Evaluation Shengran Hu Ran Cheng Cheng He Zhichao Lu Jing Wang Miao Zhang 32 7 0 08 Oct 2021
BR-NPA: A Non-Parametric High-Resolution Attention Model to improve the Interpretability of Attention T. Gomez Suiyi Ling Thomas Fréour Harold Mouchère 12 5 0 04 Jun 2021
Explainable Artificial Intelligence for Process Mining: A General Overview and Application of a Novel Local Explanation Approach for Predictive Process Monitoring Nijat Mehdiyev Peter Fettke AI4TS 25 55 0 04 Sep 2020
iCaps: An Interpretable Classifier via Disentangled Capsule Networks Dahuin Jung Jonghyun Lee Jihun Yi Sungroh Yoon 20 12 0 20 Aug 2020
Drug discovery with explainable artificial intelligence José Jiménez-Luna F. Grisoni G. Schneider 30 625 0 01 Jul 2020
Adversarial Infidelity Learning for Model Interpretation Jian Liang Bing Bai Yuren Cao Kun Bai Fei-Yue Wang AAML 44 18 0 09 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 44 82 0 17 Mar 2020
Ground Truth Evaluation of Neural Network Explanations with CLEVR-XAI L. Arras Ahmed Osman Wojciech Samek XAI AAML 21 150 0 16 Mar 2020
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI Alejandro Barredo Arrieta Natalia Díaz Rodríguez Javier Del Ser Adrien Bennetot S. Tabik ... S. Gil-Lopez Daniel Molina Richard Benjamins Raja Chatila Francisco Herrera XAI 37 6,110 0 22 Oct 2019
Sanity Checks for Saliency Maps Julius Adebayo Justin Gilmer M. Muelly Ian Goodfellow Moritz Hardt Been Kim FAtt AAML XAI 35 1,927 0 08 Oct 2018
xGEMs: Generating Examplars to Explain Black-Box Models Shalmali Joshi Oluwasanmi Koyejo Been Kim Joydeep Ghosh MLAU 25 40 0 22 Jun 2018
A Note about: Local Explanation Methods for Deep Neural Networks lack Sensitivity to Parameter Values Mukund Sundararajan Ankur Taly FAtt 11 21 0 11 Jun 2018
Bioinformatics and Medicine in the Era of Deep Learning D. Bacciu P. Lisboa José D. Martín R. Stoean A. Vellido AI4CE BDL 33 17 0 27 Feb 2018
Interpretability Beyond Feature Attribution: Quantitative Testing with Concept Activation Vectors (TCAV) Been Kim Martin Wattenberg Justin Gilmer Carrie J. Cai James Wexler F. Viégas Rory Sayres FAtt 77 1,791 0 30 Nov 2017