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Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers

2 January 2025

Papers citing "Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers"

27 / 27 papers shown

Title
EU-Nets: Enhanced, Explainable and Parsimonious U-Nets B. Sun P. Liò 112 0 0 25 Feb 2025
ViT-CX: Causal Explanation of Vision Transformers Weiyan Xie Xiao-hui Li Caleb Chen Cao Nevin L.Zhang ViT 111 20 0 06 Nov 2022
Transformers in Medical Imaging: A Survey Fahad Shamshad Salman Khan Syed Waqas Zamir Muhammad Haris Khan Munawar Hayat Fahad Shahbaz Khan Huazhu Fu ViT LM&MA MedIm 197 712 0 24 Jan 2022
A ConvNet for the 2020s Zhuang Liu Hanzi Mao Chaozheng Wu Christoph Feichtenhofer Trevor Darrell Saining Xie ViT 204 5,281 0 10 Jan 2022
MedMNIST v2 -- A large-scale lightweight benchmark for 2D and 3D biomedical image classification Jiancheng Yang Rui Shi D. Wei Zequan Liu Lin Zhao B. Ke Hanspeter Pfister Bingbing Ni VLM 328 709 0 27 Oct 2021
MobileViT: Light-weight, General-purpose, and Mobile-friendly Vision Transformer Sachin Mehta Mohammad Rastegari ViT 305 1,306 0 05 Oct 2021
U-Net Transformer: Self and Cross Attention for Medical Image Segmentation Olivier Petit Nicolas Thome Clément Rambour L. Soler ViT MedIm 113 251 0 10 Mar 2021
Eigen-CAM: Class Activation Map using Principal Components Mohammed Bany Muhammad M. Yeasin 83 346 0 01 Aug 2020
Quantifying Attention Flow in Transformers Samira Abnar Willem H. Zuidema 199 808 0 02 May 2020
Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural Networks Mehdi Neshat Zifan Wang Bradley Alexander Fan Yang Zijian Zhang Sirui Ding Markus Wagner Helen Zhou FAtt 116 1,080 0 03 Oct 2019
Revealing the Dark Secrets of BERT Olga Kovaleva Alexey Romanov Anna Rogers Anna Rumshisky 96 556 0 21 Aug 2019
What Does BERT Look At? An Analysis of BERT's Attention Kevin Clark Urvashi Khandelwal Omer Levy Christopher D. Manning MILM 319 1,610 0 11 Jun 2019
Attention is not Explanation Sarthak Jain Byron C. Wallace FAtt 176 1,333 0 26 Feb 2019
Attention Gated Networks: Learning to Leverage Salient Regions in Medical Images Jo Schlemper Ozan Oktay M. Schaap M. Heinrich Bernhard Kainz Ben Glocker Daniel Rueckert MedIm 127 1,488 0 22 Aug 2018
CBAM: Convolutional Block Attention Module Sanghyun Woo Jongchan Park Joon-Young Lee In So Kweon 242 16,797 0 17 Jul 2018
RISE: Randomized Input Sampling for Explanation of Black-box Models Vitali Petsiuk Abir Das Kate Saenko FAtt 255 1,181 0 19 Jun 2018
Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks Aditya Chattopadhyay Anirban Sarkar Prantik Howlader V. Balasubramanian FAtt 147 2,331 0 30 Oct 2017
Graph Attention Networks Petar Velickovic Guillem Cucurull Arantxa Casanova Adriana Romero Pietro Lio Yoshua Bengio GNN 811 20,404 0 30 Oct 2017
Squeeze-and-Excitation Networks Jie Hu Li Shen Samuel Albanie Gang Sun Enhua Wu 529 26,778 0 05 Sep 2017
Attention Is All You Need Ashish Vaswani Noam M. Shazeer Niki Parmar Jakob Uszkoreit Llion Jones Aidan Gomez Lukasz Kaiser Illia Polosukhin 3DV 1.0K 133,589 0 12 Jun 2017
A Unified Approach to Interpreting Model Predictions Scott M. Lundberg Su-In Lee FAtt 1.4K 22,397 0 22 May 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 356 6,064 0 04 Mar 2017
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 646 20,290 0 07 Oct 2016
Semi-Supervised Classification with Graph Convolutional Networks Thomas Kipf Max Welling GNN SSL 819 29,331 0 09 Sep 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.7K 195,301 0 10 Dec 2015
U-Net: Convolutional Networks for Biomedical Image Segmentation Olaf Ronneberger Philipp Fischer Thomas Brox SSeg 3DV 2.1K 77,887 0 18 May 2015
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 425 4,685 0 21 Dec 2014