Robust Explainability: A Tutorial on Gradient-Based Attribution Methods
for Deep Neural Networks

Robust Explainability: A Tutorial on Gradient-Based Attribution Methods for Deep Neural Networks

23 July 2021

R. Ramachandran

Papers citing "Robust Explainability: A Tutorial on Gradient-Based Attribution Methods for Deep Neural Networks"

13 / 13 papers shown

Title
Human-inspired Explanations for Vision Transformers and Convolutional Neural Networks Mahadev Prasad Panda Matteo Tiezzi Martina Vilas Gemma Roig Bjoern M. Eskofier Dario Zanca ViT AAML 41 1 0 04 Aug 2024
Stability of Explainable Recommendation Sairamvinay Vijayaraghavan Prasant Mohapatra AAML 40 1 0 03 May 2024
Feature Attribution with Necessity and Sufficiency via Dual-stage Perturbation Test for Causal Explanation Xuexin Chen Ruichu Cai Zhengting Huang Yuxuan Zhu Julien Horwood Zhifeng Hao Zijian Li Jose Miguel Hernandez-Lobato AAML 38 2 0 13 Feb 2024
Robust Ranking Explanations Chao Chen Chenghua Guo Guixiang Ma Ming Zeng Xi Zhang Sihong Xie FAtt AAML 37 0 0 08 Jul 2023
Towards Explainable AI for Channel Estimation in Wireless Communications Abdul Karim Gizzini Y. Medjahdi A. Ghandour Laurent Clavier 6 15 0 03 Jul 2023
Multimodal Data Integration for Oncology in the Era of Deep Neural Networks: A Review Asim Waqas Aakash Tripathi Ravichandran Ramachandran Paul Stewart Ghulam Rasool AI4CE 42 32 0 11 Mar 2023
Tracr: Compiled Transformers as a Laboratory for Interpretability David Lindner János Kramár Sebastian Farquhar Matthew Rahtz Tom McGrath Vladimir Mikulik 34 72 0 12 Jan 2023
Privacy Meets Explainability: A Comprehensive Impact Benchmark S. Saifullah Dominique Mercier Adriano Lucieri Andreas Dengel Sheraz Ahmed 35 14 0 08 Nov 2022
Explainable Deep Learning to Profile Mitochondrial Disease Using High Dimensional Protein Expression Data Atif Khan C. Lawless Amy Vincent Satish Pilla S. Ramesh A. Mcgough 36 0 0 31 Oct 2022
Toward Transparent AI: A Survey on Interpreting the Inner Structures of Deep Neural Networks Tilman Raukur A. Ho Stephen Casper Dylan Hadfield-Menell AAML AI4CE 28 124 0 27 Jul 2022
Trustworthy Graph Neural Networks: Aspects, Methods and Trends He Zhang Bang Wu Xingliang Yuan Shirui Pan Hanghang Tong Jian Pei 45 104 0 16 May 2022
Time to Focus: A Comprehensive Benchmark Using Time Series Attribution Methods Dominique Mercier Jwalin Bhatt Andreas Dengel Sheraz Ahmed AI4TS 22 11 0 08 Feb 2022
EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: the MonuMAI cultural heritage use case Natalia Díaz Rodríguez Alberto Lamas Jules Sanchez Gianni Franchi Ivan Donadello Siham Tabik David Filliat P. Cruz Rosana Montes Francisco Herrera 49 77 0 24 Apr 2021