Network Dissection: Quantifying Interpretability of Deep Visual Representations

19 April 2017

Antonio Torralba

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

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Title
Neural View Synthesis and Matching for Semi-Supervised Few-Shot Learning of 3D Pose Angtian Wang Shenxiao Mei Alan Yuille Adam Kortylewski 3DV 13 21 0 27 Oct 2021
StyleAlign: Analysis and Applications of Aligned StyleGAN Models Zongze Wu Yotam Nitzan Eli Shechtman Dani Lischinski 16 56 0 21 Oct 2021
Quantifying Local Specialization in Deep Neural Networks Shlomi Hod Daniel Filan Stephen Casper Andrew Critch Stuart J. Russell 60 10 0 13 Oct 2021
Robust Feature-Level Adversaries are Interpretability Tools Stephen Casper Max Nadeau Dylan Hadfield-Menell Gabriel Kreiman AAML 40 27 0 07 Oct 2021
Explaining Convolutional Neural Networks by Tagging Filters Anna Nguyen Daniel Hagenmayer T. Weller Michael Färber FAtt 17 0 0 20 Sep 2021
Understanding of Kernels in CNN Models by Suppressing Irrelevant Visual Features in Images Jiafan Zhuang Wanying Tao Jianfei Xing Wei Shi Ruixuan Wang Weishi Zheng FAtt 32 3 0 25 Aug 2021
Interpreting Face Inference Models using Hierarchical Network Dissection Divyang Teotia Àgata Lapedriza Sarah Ostadabbas CVBM 22 3 0 23 Aug 2021
COVID-view: Diagnosis of COVID-19 using Chest CT Shreeraj Jadhav Gaofeng Deng M. Zawin Arie Kaufman 38 18 0 09 Aug 2021
Spatiotemporal Contrastive Learning of Facial Expressions in Videos Shuvendu Roy Ali Etemad 32 17 0 06 Aug 2021
What do End-to-End Speech Models Learn about Speaker, Language and Channel Information? A Layer-wise and Neuron-level Analysis Shammur A. Chowdhury Nadir Durrani Ahmed M. Ali 25 12 0 01 Jul 2021
Inverting and Understanding Object Detectors Ang Cao Justin Johnson ObjD 10 3 0 26 Jun 2021
Evaluation of Saliency-based Explainability Method Sam Zabdiel Sunder Samuel V. Kamakshi Namrata Lodhi N. C. Krishnan FAtt XAI 21 12 0 24 Jun 2021
3DB: A Framework for Debugging Computer Vision Models Guillaume Leclerc Hadi Salman Andrew Ilyas Sai H. Vemprala Logan Engstrom ... Pengchuan Zhang Shibani Santurkar Greg Yang Ashish Kapoor A. Madry 38 40 0 07 Jun 2021
A Comprehensive Taxonomy for Explainable Artificial Intelligence: A Systematic Survey of Surveys on Methods and Concepts Gesina Schwalbe Bettina Finzel XAI 21 184 0 15 May 2021
Leveraging Sparse Linear Layers for Debuggable Deep Networks Eric Wong Shibani Santurkar A. Madry FAtt 20 88 0 11 May 2021
Rationalization through Concepts Diego Antognini Boi Faltings FAtt 11 19 0 11 May 2021
Do Feature Attribution Methods Correctly Attribute Features? Yilun Zhou Serena Booth Marco Tulio Ribeiro J. Shah FAtt XAI 22 132 0 27 Apr 2021
Exploiting Explanations for Model Inversion Attacks Xu Zhao Wencan Zhang Xiao Xiao Brian Y. Lim MIACV 21 82 0 26 Apr 2021
Equivariant Wavelets: Fast Rotation and Translation Invariant Wavelet Scattering Transforms A. Saydjari D. Finkbeiner 17 20 0 22 Apr 2021
An Interpretability Illusion for BERT Tolga Bolukbasi Adam Pearce Ann Yuan Andy Coenen Emily Reif Fernanda Viégas Martin Wattenberg MILM FAtt 24 68 0 14 Apr 2021
EX-RAY: Distinguishing Injected Backdoor from Natural Features in Neural Networks by Examining Differential Feature Symmetry Yingqi Liu Guangyu Shen Guanhong Tao Zhenting Wang Shiqing Ma X. Zhang AAML 22 8 0 16 Mar 2021
Explainability of deep vision-based autonomous driving systems: Review and challenges Éloi Zablocki H. Ben-younes P. Pérez Matthieu Cord XAI 32 169 0 13 Jan 2021
Debiased-CAM to mitigate image perturbations with faithful visual explanations of machine learning Wencan Zhang Mariella Dimiccoli Brian Y. Lim FAtt 16 18 0 10 Dec 2020
StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation Zongze Wu Dani Lischinski Eli Shechtman DRL 49 482 0 25 Nov 2020
Teaching with Commentaries Aniruddh Raghu M. Raghu Simon Kornblith D. Duvenaud Geoffrey E. Hinton 12 24 0 05 Nov 2020
This Looks Like That, Because ... Explaining Prototypes for Interpretable Image Recognition Meike Nauta Annemarie Jutte Jesper C. Provoost C. Seifert FAtt 14 65 0 05 Nov 2020
Quantifying Learnability and Describability of Visual Concepts Emerging in Representation Learning Iro Laina Ruth C. Fong Andrea Vedaldi OCL 20 13 0 27 Oct 2020
Exemplary Natural Images Explain CNN Activations Better than State-of-the-Art Feature Visualization Judy Borowski Roland S. Zimmermann Judith Schepers Robert Geirhos Thomas S. A. Wallis Matthias Bethge Wieland Brendel FAtt 34 7 0 23 Oct 2020
The Intriguing Relation Between Counterfactual Explanations and Adversarial Examples Timo Freiesleben GAN 27 62 0 11 Sep 2020
CuratorNet: Visually-aware Recommendation of Art Images Pablo Messina Manuel Cartagena Patricio Cerda Felipe del-Rio Denis Parra 12 14 0 09 Sep 2020
Axiom-based Grad-CAM: Towards Accurate Visualization and Explanation of CNNs Ruigang Fu Qingyong Hu Xiaohu Dong Yulan Guo Yinghui Gao Biao Li FAtt 18 266 0 05 Aug 2020
Explainable Face Recognition Jonathan R. Williford Brandon B. May J. Byrne CVBM 16 71 0 03 Aug 2020
Interpretable Anomaly Detection with DIFFI: Depth-based Isolation Forest Feature Importance Mattia Carletti M. Terzi Gian Antonio Susto 23 42 0 21 Jul 2020
Training Interpretable Convolutional Neural Networks by Differentiating Class-specific Filters Haoyun Liang Zhihao Ouyang Yuyuan Zeng Hang Su Zihao He Shutao Xia Jun Zhu Bo Zhang 16 47 0 16 Jul 2020
Scientific Discovery by Generating Counterfactuals using Image Translation Arunachalam Narayanaswamy Subhashini Venugopalan D. Webster L. Peng G. Corrado ... Abigail E. Huang Siva Balasubramanian Michael P. Brenner Phil Q. Nelson A. Varadarajan DiffM MedIm 20 20 0 10 Jul 2020
Proper Network Interpretability Helps Adversarial Robustness in Classification Akhilan Boopathy Sijia Liu Gaoyuan Zhang Cynthia Liu Pin-Yu Chen Shiyu Chang Luca Daniel AAML FAtt 10 66 0 26 Jun 2020
GAN Memory with No Forgetting Yulai Cong Miaoyun Zhao Jianqiao Li Sijia Wang Lawrence Carin CLL 11 116 0 13 Jun 2020
Learning to Branch for Multi-Task Learning Pengsheng Guo Chen-Yu Lee Daniel Ulbricht 13 174 0 02 Jun 2020
Interpretable and Accurate Fine-grained Recognition via Region Grouping Zixuan Huang Yin Li 8 138 0 21 May 2020
Under the Hood of Neural Networks: Characterizing Learned Representations by Functional Neuron Populations and Network Ablations Richard Meyes Constantin Waubert de Puiseau Andres Felipe Posada-Moreno Tobias Meisen AI4CE 22 22 0 02 Apr 2020
A Survey of Deep Learning for Scientific Discovery M. Raghu Erica Schmidt OOD AI4CE 35 120 0 26 Mar 2020
Foundations of Explainable Knowledge-Enabled Systems Shruthi Chari Daniel Gruen O. Seneviratne D. McGuinness 31 28 0 17 Mar 2020
TIME: A Transparent, Interpretable, Model-Adaptive and Explainable Neural Network for Dynamic Physical Processes Gurpreet Singh Soumyajit Gupta Matt Lease Clint Dawson AI4TS AI4CE 6 2 0 05 Mar 2020
Selectivity considered harmful: evaluating the causal impact of class selectivity in DNNs Matthew L. Leavitt Ari S. Morcos 50 33 0 03 Mar 2020
On Leveraging Pretrained GANs for Generation with Limited Data Miaoyun Zhao Yulai Cong Lawrence Carin 20 21 0 26 Feb 2020
Neuron Shapley: Discovering the Responsible Neurons Amirata Ghorbani James Y. Zou FAtt TDI 17 108 0 23 Feb 2020
Bridging the Gap: Providing Post-Hoc Symbolic Explanations for Sequential Decision-Making Problems with Inscrutable Representations S. Sreedharan Utkarsh Soni Mudit Verma Siddharth Srivastava S. Kambhampati 63 30 0 04 Feb 2020
Keeping Community in the Loop: Understanding Wikipedia Stakeholder Values for Machine Learning-Based Systems C. E. Smith Bowen Yu Anjali Srivastava Aaron L Halfaker Loren G. Terveen Haiyi Zhu KELM 6 69 0 14 Jan 2020
On Interpretability of Artificial Neural Networks: A Survey Fenglei Fan Jinjun Xiong Mengzhou Li Ge Wang AAML AI4CE 30 300 0 08 Jan 2020
TAB-VCR: Tags and Attributes based Visual Commonsense Reasoning Baselines Jingxiang Lin Unnat Jain A. Schwing LRM ReLM 26 9 0 31 Oct 2019