Gradient Backpropagation based Feature Attribution to Enable Explainable-AI on the Edge

19 October 2022

Papers citing "Gradient Backpropagation based Feature Attribution to Enable Explainable-AI on the Edge"

11 / 11 papers shown

Title
ApproXAI: Energy-Efficient Hardware Acceleration of Explainable AI using Approximate Computing Ayesha Siddique Khurram Khalil K. A. Hoque 49 0 0 24 Apr 2025
Accurate Explanation Model for Image Classifiers using Class Association Embedding Ruitao Xie Jingbang Chen Limai Jiang Rui Xiao Yi-Lun Pan Yunpeng Cai 237 4 0 31 Dec 2024
Hardware Acceleration of Explainable Machine Learning using Tensor Processing Units Zhixin Pan Prabhat Mishra 64 18 0 22 Mar 2021
Explainable Deep Learning: A Field Guide for the Uninitiated Gabrielle Ras Ning Xie Marcel van Gerven Derek Doran AAML XAI 111 379 0 30 Apr 2020
Automatic Compiler Based FPGA Accelerator for CNN Training S. Venkataramanaiah Yufei Ma Shihui Yin Eriko Nurvitadhi A. Dasu Yu Cao Jae-sun Seo 62 37 0 15 Aug 2019
iNNvestigate neural networks! Maximilian Alber Sebastian Lapuschkin P. Seegerer Miriam Hagele Kristof T. Schütt G. Montavon Wojciech Samek K. Müller Sven Dähne Pieter-Jan Kindermans 70 348 0 13 Aug 2018
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization Ramprasaath R. Selvaraju Michael Cogswell Abhishek Das Ramakrishna Vedantam Devi Parikh Dhruv Batra FAtt 357 20,136 0 07 Oct 2016
SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size F. Iandola Song Han Matthew W. Moskewicz Khalid Ashraf W. Dally Kurt Keutzer 167 7,503 0 24 Feb 2016
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 254 4,683 0 21 Dec 2014
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 326 7,321 0 20 Dec 2013
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 607 15,907 0 12 Nov 2013