PAMI: partition input and aggregate outputs for model interpretation

7 February 2023

Papers citing "PAMI: partition input and aggregate outputs for model interpretation"

50 / 61 papers shown

Title
FCN-Transformer Feature Fusion for Polyp Segmentation Edward Sanderson B. Matuszewski ViT MedIm 49 119 0 17 Aug 2022
TransCAM: Transformer Attention-based CAM Refinement for Weakly Supervised Semantic Segmentation Ruiwen Li Zheda Mai C. Trabelsi Zhibo Zhang Jongseong Jang Scott Sanner ViT 33 61 0 14 Mar 2022
A ConvNet for the 2020s Zhuang Liu Hanzi Mao Chaozheng Wu Christoph Feichtenhofer Trevor Darrell Saining Xie ViT 67 5,102 0 10 Jan 2022
ClipCap: CLIP Prefix for Image Captioning Ron Mokady Amir Hertz Amit H. Bermano CLIP VLM 52 668 0 18 Nov 2021
BERT, mBERT, or BiBERT? A Study on Contextualized Embeddings for Neural Machine Translation Haoran Xu Benjamin Van Durme Kenton W. Murray 55 58 0 09 Sep 2021
This looks more like that: Enhancing Self-Explaining Models by Prototypical Relevance Propagation Srishti Gautam Marina M.-C. Höhne Stine Hansen Robert Jenssen Michael C. Kampffmeyer 37 49 0 27 Aug 2021
R-Drop: Regularized Dropout for Neural Networks Xiaobo Liang Lijun Wu Juntao Li Yue Wang Qi Meng Tao Qin Wei Chen Hao Fei Tie-Yan Liu 62 430 0 28 Jun 2021
Medical Image Segmentation Using Squeeze-and-Expansion Transformers Shaohua Li Xiuchao Sui Xiangde Luo Xinxing Xu Yong Liu Rick Siow Mong Goh ViT MedIm 42 167 0 20 May 2021
Rethinking Perturbations in Encoder-Decoders for Fast Training Sho Takase Shun Kiyono 49 45 0 05 Apr 2021
Building Reliable Explanations of Unreliable Neural Networks: Locally Smoothing Perspective of Model Interpretation Dohun Lim Hyeonseok Lee Sungchan Kim FAtt AAML 41 13 0 26 Mar 2021
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows Ze Liu Yutong Lin Yue Cao Han Hu Yixuan Wei Zheng Zhang Stephen Lin B. Guo ViT 327 21,175 0 25 Mar 2021
Believe The HiPe: Hierarchical Perturbation for Fast, Robust, and Model-Agnostic Saliency Mapping Jessica Cooper Ognjen Arandjelovic David J. Harrison AAML 108 13 0 22 Feb 2021
Visual explanation of black-box model: Similarity Difference and Uniqueness (SIDU) method Satya M. Muddamsetty M. N. Jahromi Andreea-Emilia Ciontos Laura M. Fenoy T. Moeslund AAML 63 26 0 26 Jan 2021
Transformer Interpretability Beyond Attention Visualization Hila Chefer Shir Gur Lior Wolf 77 652 0 17 Dec 2020
Neural Prototype Trees for Interpretable Fine-grained Image Recognition Meike Nauta Ron van Bree C. Seifert 122 263 0 03 Dec 2020
ProtoPShare: Prototype Sharing for Interpretable Image Classification and Similarity Discovery Dawid Rymarczyk Lukasz Struski Jacek Tabor Bartosz Zieliñski 31 112 0 29 Nov 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 400 40,217 0 22 Oct 2020
Captum: A unified and generic model interpretability library for PyTorch Narine Kokhlikyan Vivek Miglani Miguel Martin Edward Wang B. Alsallakh ... Alexander Melnikov Natalia Kliushkina Carlos Araya Siqi Yan Orion Reblitz-Richardson FAtt 116 829 0 16 Sep 2020
Understanding the Role of Individual Units in a Deep Neural Network David Bau Jun-Yan Zhu Hendrik Strobelt Àgata Lapedriza Bolei Zhou Antonio Torralba GAN 45 446 0 10 Sep 2020
GroupFace: Learning Latent Groups and Constructing Group-based Representations for Face Recognition Y. Kim Wonpyo Park Myung-Cheol Roh Jongju Shin CVBM 74 88 0 21 May 2020
Designing Network Design Spaces Ilija Radosavovic Raj Prateek Kosaraju Ross B. Girshick Kaiming He Piotr Dollár GNN 84 1,672 0 30 Mar 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 277 42,038 0 03 Dec 2019
VarGFaceNet: An Efficient Variable Group Convolutional Neural Network for Lightweight Face Recognition Mengjia Yan Mengao Zhao Zining Xu Qian Zhang Guoli Wang Zhizhong Su CVBM 51 92 0 11 Oct 2019
Score-CAM: Score-Weighted Visual Explanations for Convolutional Neural Networks Mehdi Neshat Zifan Wang Bradley Alexander Fan Yang Zijian Zhang Sirui Ding Markus Wagner Xia Hu FAtt 72 1,056 0 03 Oct 2019
Explaining Convolutional Neural Networks using Softmax Gradient Layer-wise Relevance Propagation Brian Kenji Iwana Ryohei Kuroki S. Uchida FAtt 40 96 0 06 Aug 2019
Understanding the Representation Power of Graph Neural Networks in Learning Graph Topology Nima Dehmamy Albert-László Barabási Rose Yu GNN 82 133 0 11 Jul 2019
Graph Neural Network for Interpreting Task-fMRI Biomarkers Xiaoxiao Li Nicha Dvornek Yuan Zhou Juntang Zhuang P. Ventola James S. Duncan 49 102 0 02 Jul 2019
Full-Gradient Representation for Neural Network Visualization Suraj Srinivas François Fleuret MILM FAtt 63 271 0 02 May 2019
Med3D: Transfer Learning for 3D Medical Image Analysis Sihong Chen Kai Ma Yefeng Zheng MedIm 52 454 0 01 Apr 2019
Understanding Individual Decisions of CNNs via Contrastive Backpropagation Jindong Gu Yinchong Yang Volker Tresp FAtt 29 94 0 05 Dec 2018
RISE: Randomized Input Sampling for Explanation of Black-box Models Vitali Petsiuk Abir Das Kate Saenko FAtt 118 1,164 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 164 1,828 0 30 Nov 2017
Grad-CAM++: Improved Visual Explanations for Deep Convolutional Networks Aditya Chattopadhyay Anirban Sarkar Prantik Howlader V. Balasubramanian FAtt 91 2,280 0 30 Oct 2017
Squeeze-and-Excitation Networks Jie Hu Li Shen Samuel Albanie Gang Sun Enhua Wu 341 26,241 0 05 Sep 2017
Wasserstein CNN: Learning Invariant Features for NIR-VIS Face Recognition Ran He Xiang Wu Zhenan Sun Tieniu Tan CVBM 61 277 0 08 Aug 2017
SmoothGrad: removing noise by adding noise D. Smilkov Nikhil Thorat Been Kim F. Viégas Martin Wattenberg FAtt ODL 187 2,215 0 12 Jun 2017
Learning how to explain neural networks: PatternNet and PatternAttribution Pieter-Jan Kindermans Kristof T. Schütt Maximilian Alber K. Müller D. Erhan Been Kim Sven Dähne XAI FAtt 57 338 0 16 May 2017
Interpretable Explanations of Black Boxes by Meaningful Perturbation Ruth C. Fong Andrea Vedaldi FAtt AAML 50 1,514 0 11 Apr 2017
Axiomatic Attribution for Deep Networks Mukund Sundararajan Ankur Taly Qiqi Yan OOD FAtt 122 5,920 0 04 Mar 2017
Visualizing Deep Neural Network Decisions: Prediction Difference Analysis L. Zintgraf Taco S. Cohen T. Adel Max Welling FAtt 112 707 0 15 Feb 2017
Understanding the Effective Receptive Field in Deep Convolutional Neural Networks Wenjie Luo Yujia Li R. Urtasun R. Zemel HAI 68 1,789 0 15 Jan 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 216 19,796 0 07 Oct 2016
Densely Connected Convolutional Networks Gao Huang Zhuang Liu Laurens van der Maaten Kilian Q. Weinberger PINN 3DV 631 36,599 0 25 Aug 2016
Top-down Neural Attention by Excitation Backprop Jianming Zhang Zhe Lin Jonathan Brandt Xiaohui Shen Stan Sclaroff 60 946 0 01 Aug 2016
Layer-wise Relevance Propagation for Neural Networks with Local Renormalization Layers Alexander Binder G. Montavon Sebastian Lapuschkin K. Müller Wojciech Samek FAtt 54 456 0 04 Apr 2016
"Why Should I Trust You?": Explaining the Predictions of Any Classifier Marco Tulio Ribeiro Sameer Singh Carlos Guestrin FAtt FaML 587 16,828 0 16 Feb 2016
Learning Deep Features for Discriminative Localization Bolei Zhou A. Khosla Àgata Lapedriza A. Oliva Antonio Torralba SSL SSeg FAtt 170 9,280 0 14 Dec 2015
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 1.4K 192,638 0 10 Dec 2015
Explaining NonLinear Classification Decisions with Deep Taylor Decomposition G. Montavon Sebastian Lapuschkin Alexander Binder Wojciech Samek Klaus-Robert Muller FAtt 53 730 0 08 Dec 2015
Rethinking the Inception Architecture for Computer Vision Christian Szegedy Vincent Vanhoucke Sergey Ioffe Jonathon Shlens Z. Wojna 3DV BDL 497 27,231 0 02 Dec 2015