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Explaining the Impact of Training on Vision Models via Activation Clustering

29 November 2024

Papers citing "Explaining the Impact of Training on Vision Models via Activation Clustering"

43 / 43 papers shown

Title
BackMix: Mitigating Shortcut Learning in Echocardiography with Minimal Supervision Kit M. Bransby A. Beqiri Woo-Jin Cho Kim Jorge Oliveira A. Chartsias Alberto Gomez 75 1 0 27 Jun 2024
Prototypical Self-Explainable Models Without Re-training Srishti Gautam Ahcène Boubekki Marina M.-C. Höhne Michael C. Kampffmeyer 97 2 0 13 Dec 2023
Vision Transformers Need Registers Zilong Chen Maxime Oquab Julien Mairal Huaping Liu ViT 201 356 0 28 Sep 2023
Weakly-supervised Contrastive Learning for Unsupervised Object Discovery Yun-Qiu Lv Jing Zhang Nick Barnes Yuchao Dai 79 11 0 07 Jul 2023
XAI-TRIS: Non-linear image benchmarks to quantify false positive post-hoc attribution of feature importance Benedict Clark Rick Wilming Stefan Haufe 100 5 0 22 Jun 2023
A Holistic Approach to Unifying Automatic Concept Extraction and Concept Importance Estimation Thomas Fel Victor Boutin Mazda Moayeri Rémi Cadène Louis Bethune Léo Andéol Mathieu Chalvidal Thomas Serre FAtt 94 64 0 11 Jun 2023
Explain Any Concept: Segment Anything Meets Concept-Based Explanation Ao Sun Pingchuan Ma Yuanyuan Yuan Shuai Wang LLMAG 112 36 0 17 May 2023
DINOv2: Learning Robust Visual Features without Supervision Maxime Oquab Timothée Darcet Théo Moutakanni Huy Q. Vo Marc Szafraniec ... Hervé Jégou Julien Mairal Patrick Labatut Armand Joulin Piotr Bojanowski VLM CLIP SSL 448 3,529 0 14 Apr 2023
Preemptively Pruning Clever-Hans Strategies in Deep Neural Networks Lorenz Linhardt Klaus-Robert Muller G. Montavon AAML 109 8 0 12 Apr 2023
Disentangled Explanations of Neural Network Predictions by Finding Relevant Subspaces Pattarawat Chormai J. Herrmann Klaus-Robert Muller G. Montavon FAtt 120 20 0 30 Dec 2022
CRAFT: Concept Recursive Activation FacTorization for Explainability Thomas Fel Agustin Picard Louis Bethune Thibaut Boissin David Vigouroux Julien Colin Rémi Cadène Thomas Serre 103 116 0 17 Nov 2022
Demonstrating The Risk of Imbalanced Datasets in Chest X-ray Image-based Diagnostics by Prototypical Relevance Propagation Srishti Gautam Marina M.-C. Höhne Stine Hansen Robert Jenssen Michael C. Kampffmeyer 59 7 0 10 Jan 2022
RELAX: Representation Learning Explainability Kristoffer Wickstrøm Daniel J. Trosten Sigurd Løkse Ahcène Boubekki Karl Øyvind Mikalsen Michael C. Kampffmeyer Robert Jenssen FAtt 49 15 0 19 Dec 2021
Localizing Objects with Self-Supervised Transformers and no Labels Oriane Siméoni Gilles Puy Huy V. Vo Simon Roburin Spyros Gidaris Andrei Bursuc P. Pérez Renaud Marlet Jean Ponce ViT 260 203 0 29 Sep 2021
Instance-wise or Class-wise? A Tale of Neighbor Shapley for Concept-based Explanation Jiahui Li Kun Kuang Lin Li Long Chen Songyang Zhang Jian Shao Jun Xiao FAtt 106 19 0 03 Sep 2021
Emerging Properties in Self-Supervised Vision Transformers Mathilde Caron Hugo Touvron Ishan Misra Hervé Jégou Julien Mairal Piotr Bojanowski Armand Joulin 812 6,149 0 29 Apr 2021
Transformer Interpretability Beyond Attention Visualization Hila Chefer Shir Gur Lior Wolf 145 676 0 17 Dec 2020
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale Alexey Dosovitskiy Lucas Beyer Alexander Kolesnikov Dirk Weissenborn Xiaohua Zhai ... Matthias Minderer G. Heigold Sylvain Gelly Jakob Uszkoreit N. Houlsby ViT 736 41,796 0 22 Oct 2020
Explainable Face Recognition Jonathan R. Williford Brandon B. May J. Byrne CVBM 69 71 0 03 Aug 2020
Shortcut Learning in Deep Neural Networks Robert Geirhos J. Jacobsen Claudio Michaelis R. Zemel Wieland Brendel Matthias Bethge Felix Wichmann 229 2,069 0 16 Apr 2020
A Simple Framework for Contrastive Learning of Visual Representations Ting-Li Chen Simon Kornblith Mohammad Norouzi Geoffrey E. Hinton SSL 422 18,968 0 13 Feb 2020
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 632 42,770 0 03 Dec 2019
On Completeness-aware Concept-Based Explanations in Deep Neural Networks Chih-Kuan Yeh Been Kim Sercan O. Arik Chun-Liang Li Tomas Pfister Pradeep Ravikumar FAtt 316 307 0 17 Oct 2019
Explanations can be manipulated and geometry is to blame Ann-Kathrin Dombrowski Maximilian Alber Christopher J. Anders M. Ackermann K. Müller Pan Kessel AAML FAtt 88 335 0 19 Jun 2019
From Clustering to Cluster Explanations via Neural Networks Jacob R. Kauffmann Malte Esders Lukas Ruff G. Montavon Wojciech Samek K. Müller 79 72 0 18 Jun 2019
FCOS: Fully Convolutional One-Stage Object Detection Zhi Tian Chunhua Shen Hao Chen Tong He ObjD 198 5,031 0 02 Apr 2019
Unmasking Clever Hans Predictors and Assessing What Machines Really Learn Sebastian Lapuschkin S. Wäldchen Alexander Binder G. Montavon Wojciech Samek K. Müller 106 1,022 0 26 Feb 2019
Confounding variables can degrade generalization performance of radiological deep learning models J. Zech Marcus A. Badgeley Manway Liu A. Costa J. Titano Eric K. Oermann OOD 91 1,185 0 02 Jul 2018
This Looks Like That: Deep Learning for Interpretable Image Recognition Chaofan Chen Oscar Li Chaofan Tao A. Barnett Jonathan Su Cynthia Rudin 304 1,191 0 27 Jun 2018
Towards Robust Interpretability with Self-Explaining Neural Networks David Alvarez-Melis Tommi Jaakkola MILM XAI 138 948 0 20 Jun 2018
RISE: Randomized Input Sampling for Explanation of Black-box Models Vitali Petsiuk Abir Das Kate Saenko FAtt 224 1,177 0 19 Jun 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 272 1,849 0 30 Nov 2017
Interpreting Deep Visual Representations via Network Dissection Bolei Zhou David Bau A. Oliva Antonio Torralba FAtt MILM 74 325 0 15 Nov 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 213 6,044 0 04 Mar 2017
Feature Pyramid Networks for Object Detection Nayeon Lee Piotr Dollár Ross B. Girshick Kaiming He Bharath Hariharan Serge J. Belongie ObjD 528 22,242 0 09 Dec 2016
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 508 20,227 0 07 Oct 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 1.3K 17,197 0 16 Feb 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.4K 195,011 0 10 Dec 2015
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 276 4,682 0 21 Dec 2014
ImageNet Large Scale Visual Recognition Challenge Olga Russakovsky Jia Deng Hao Su J. Krause S. Satheesh ... A. Karpathy A. Khosla Michael S. Bernstein Alexander C. Berg Li Fei-Fei VLM ObjD 1.7K 39,705 0 01 Sep 2014
Microsoft COCO: Common Objects in Context Nayeon Lee Michael Maire Serge J. Belongie Lubomir Bourdev Ross B. Girshick James Hays Pietro Perona Deva Ramanan C. L. Zitnick Piotr Dollár ObjD 473 43,961 0 01 May 2014
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 339 7,333 0 20 Dec 2013
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 633 15,922 0 12 Nov 2013