Network Dissection: Quantifying Interpretability of Deep Visual Representations

19 April 2017

Antonio Torralba

Papers citing "Network Dissection: Quantifying Interpretability of Deep Visual Representations"

50 / 294 papers shown

Title
MadEye: Boosting Live Video Analytics Accuracy with Adaptive Camera Configurations M. Wong M. Ramanujam Guha Balakrishnan Ravi Netravali 36 4 0 04 Apr 2023
Implicit Visual Bias Mitigation by Posterior Estimate Sharpening of a Bayesian Neural Network Rebecca S Stone Nishant Ravikumar A. Bulpitt David C. Hogg BDL 41 0 0 29 Mar 2023
UFO: A unified method for controlling Understandability and Faithfulness Objectives in concept-based explanations for CNNs V. V. Ramaswamy Sunnie S. Y. Kim Ruth C. Fong Olga Russakovsky 40 0 0 27 Mar 2023
LINe: Out-of-Distribution Detection by Leveraging Important Neurons Yong Hyun Ahn Gyeong-Moon Park Seong Tae Kim OODD 119 31 0 24 Mar 2023
Take 5: Interpretable Image Classification with a Handful of Features Thomas Norrenbrock Marco Rudolph Bodo Rosenhahn FAtt 42 7 0 23 Mar 2023
SUNY: A Visual Interpretation Framework for Convolutional Neural Networks from a Necessary and Sufficient Perspective Xiwei Xuan Ziquan Deng Hsuan-Tien Lin Z. Kong Kwan-Liu Ma AAML FAtt 43 2 0 01 Mar 2023
Does a Neural Network Really Encode Symbolic Concepts? Mingjie Li Quanshi Zhang 34 30 0 25 Feb 2023
Holistically Explainable Vision Transformers Moritz D Boehle Mario Fritz Bernt Schiele ViT 41 9 0 20 Jan 2023
Rationalizing Predictions by Adversarial Information Calibration Lei Sha Oana-Maria Camburu Thomas Lukasiewicz 30 4 0 15 Jan 2023
GH-Feat: Learning Versatile Generative Hierarchical Features from GANs Yinghao Xu Yujun Shen Jiapeng Zhu Ceyuan Yang Bolei Zhou 31 2 0 12 Jan 2023
Tracr: Compiled Transformers as a Laboratory for Interpretability David Lindner János Kramár Sebastian Farquhar Matthew Rahtz Tom McGrath Vladimir Mikulik 36 72 0 12 Jan 2023
Disentangled Explanations of Neural Network Predictions by Finding Relevant Subspaces Pattarawat Chormai J. Herrmann Klaus-Robert Muller G. Montavon FAtt 52 18 0 30 Dec 2022
AutoSlicer: Scalable Automated Data Slicing for ML Model Analysis Zifan Liu Evan Rosen P. Suganthan 24 1 0 18 Dec 2022
Going Beyond XAI: A Systematic Survey for Explanation-Guided Learning Yuyang Gao Siyi Gu Junji Jiang S. Hong Dazhou Yu Liang Zhao 31 39 0 07 Dec 2022
Interactive Visual Feature Search Devon Ulrich Ruth C. Fong FAtt 31 0 0 28 Nov 2022
Overcoming Catastrophic Forgetting by XAI Giang Nguyen 18 0 0 25 Nov 2022
Interpreting Neural Networks through the Polytope Lens Sid Black Lee D. Sharkey Léo Grinsztajn Eric Winsor Daniel A. Braun ... Kip Parker Carlos Ramón Guevara Beren Millidge Gabriel Alfour Connor Leahy FAtt MILM 33 22 0 22 Nov 2022
Language in a Bottle: Language Model Guided Concept Bottlenecks for Interpretable Image Classification Yue Yang Artemis Panagopoulou Shenghao Zhou Daniel Jin Chris Callison-Burch Mark Yatskar 54 214 0 21 Nov 2022
Concept-based Explanations using Non-negative Concept Activation Vectors and Decision Tree for CNN Models Gayda Mutahar Tim Miller FAtt 29 6 0 19 Nov 2022
Diagnostics for Deep Neural Networks with Automated Copy/Paste Attacks Stephen Casper K. Hariharan Dylan Hadfield-Menell AAML 28 11 0 18 Nov 2022
Explainability Via Causal Self-Talk Nicholas A. Roy Junkyung Kim Neil C. Rabinowitz CML 29 7 0 17 Nov 2022
Finding Skill Neurons in Pre-trained Transformer-based Language Models Xiaozhi Wang Kaiyue Wen Zhengyan Zhang Lei Hou Zhiyuan Liu Juanzi Li MILM MoE 34 51 0 14 Nov 2022
RadFormer: Transformers with Global-Local Attention for Interpretable and Accurate Gallbladder Cancer Detection Soumen Basu Mayank Gupta Pratyaksha Rana Pankaj Gupta Chetan Arora ViT MedIm 32 32 0 09 Nov 2022
Computational pathology in renal disease: a comprehensive perspective M. Cossio MedIm 33 1 0 18 Oct 2022
Understanding CNN Fragility When Learning With Imbalanced Data Damien Dablain Kristen N. Jacobson C. Bellinger Mark Roberts Nitesh Chawla 36 39 0 17 Oct 2022
TCNL: Transparent and Controllable Network Learning Via Embedding Human-Guided Concepts Zhihao Wang Chuang Zhu 29 1 0 07 Oct 2022
"Help Me Help the AI": Understanding How Explainability Can Support Human-AI Interaction Sunnie S. Y. Kim E. A. Watkins Olga Russakovsky Ruth C. Fong Andrés Monroy-Hernández 43 108 0 02 Oct 2022
An Interactive Interpretability System for Breast Cancer Screening with Deep Learning Yuzhe Lu Adam Perer 36 3 0 30 Sep 2022
Explainable AI for clinical and remote health applications: a survey on tabular and time series data Flavio Di Martino Franca Delmastro AI4TS 33 91 0 14 Sep 2022
DASH: Visual Analytics for Debiasing Image Classification via User-Driven Synthetic Data Augmentation Bum Chul Kwon Jungsoo Lee Chaeyeon Chung Nyoungwoo Lee Ho-Jin Choi Jaegul Choo 39 10 0 14 Sep 2022
Concept-Based Explanations for Tabular Data Varsha Pendyala Jihye Choi FaML XAI FAtt 34 3 0 13 Sep 2022
TFN: An Interpretable Neural Network with Time-Frequency Transform Embedded for Intelligent Fault Diagnosis Qian Chen Xingjian Dong Guowei Tu Dong Wang Baoxuan Zhao Zhike Peng AI4CE 21 66 0 05 Sep 2022
Global Concept-Based Interpretability for Graph Neural Networks via Neuron Analysis Xuanyuan Han Pietro Barbiero Dobrik Georgiev Lucie Charlotte Magister Pietro Lio MILM 42 41 0 22 Aug 2022
Causality-Inspired Taxonomy for Explainable Artificial Intelligence Pedro C. Neto Tiago B. Gonccalves João Ribeiro Pinto W. Silva Ana F. Sequeira Arun Ross Jaime S. Cardoso XAI 43 12 0 19 Aug 2022
Regression modelling of spatiotemporal extreme U.S. wildfires via partially-interpretable neural networks J. Richards Raphael Huser 28 13 0 16 Aug 2022
Visual Interpretable and Explainable Deep Learning Models for Brain Tumor MRI and COVID-19 Chest X-ray Images Yusuf Brima M. Atemkeng FAtt MedIm 36 0 0 01 Aug 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 28 125 0 27 Jul 2022
Activation Template Matching Loss for Explainable Face Recognition Huawei Lin Haozhe Liu Qiufu Li Linlin Shen CVBM 31 1 0 05 Jul 2022
Improving Semantic Segmentation in Transformers using Hierarchical Inter-Level Attention Gary Leung Jun Gao Fangyin Wei Sanja Fidler 23 3 0 05 Jul 2022
GLANCE: Global to Local Architecture-Neutral Concept-based Explanations Avinash Kori Ben Glocker Francesca Toni 35 6 0 05 Jul 2022
Distilling Model Failures as Directions in Latent Space Saachi Jain Hannah Lawrence Ankur Moitra A. Madry 23 90 0 29 Jun 2022
Explaining Any ML Model? -- On Goals and Capabilities of XAI Moritz Renftle Holger Trittenbach M. Poznic Reinhard Heil ELM 21 4 0 28 Jun 2022
When are Post-hoc Conceptual Explanations Identifiable? Tobias Leemann Michael Kirchhof Yao Rong Enkelejda Kasneci Gjergji Kasneci 57 10 0 28 Jun 2022
RES: A Robust Framework for Guiding Visual Explanation Yuyang Gao Tong Sun Guangji Bai Siyi Gu S. Hong Liang Zhao FAtt AAML XAI 34 32 0 27 Jun 2022
Coupling Visual Semantics of Artificial Neural Networks and Human Brain Function via Synchronized Activations Lin Zhao Haixing Dai Zihao Wu Zhe Xiao Lu Zhang ... Xintao Hu Xi Jiang Sheng Li Dajiang Zhu Tianming Liu 33 8 0 22 Jun 2022
DORA: Exploring Outlier Representations in Deep Neural Networks Kirill Bykov Mayukh Deb Dennis Grinwald Klaus-Robert Muller Marina M.-C. Höhne 27 12 0 09 Jun 2022
From Attribution Maps to Human-Understandable Explanations through Concept Relevance Propagation Reduan Achtibat Maximilian Dreyer Ilona Eisenbraun S. Bosse Thomas Wiegand Wojciech Samek Sebastian Lapuschkin FAtt 36 134 0 07 Jun 2022
Post-hoc Concept Bottleneck Models Mert Yuksekgonul Maggie Wang James Zou 145 188 0 31 May 2022
On the Symmetries of Deep Learning Models and their Internal Representations Charles Godfrey Davis Brown Tegan H. Emerson Henry Kvinge 28 40 0 27 May 2022
How explainable are adversarially-robust CNNs? Mehdi Nourelahi Lars Kotthoff Peijie Chen Anh Totti Nguyen AAML FAtt 24 8 0 25 May 2022