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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TSXplain: Demystification of DNN Decisions for Time-Series using Natural Language and Statistical FeaturesInternational Conference on Artificial Neural Networks (ICANN), 2019 Mohsin Munir Shoaib Ahmed Siddiqui Ferdinand Küsters Dominique Mercier Andreas Dengel Sheraz Ahmed AI4TS 99 19 0 15 May 2019
Neurons Activation Visualization and Information Theoretic Analysis Longwei Wang Peijie Chen 82 1 0 14 May 2019
Deep Visual City Recognition Visualization Xiangwei Shi Seyran Khademi Jan van Gemert SSL HAI FAtt 91 5 0 06 May 2019
SCOPS: Self-Supervised Co-Part SegmentationComputer Vision and Pattern Recognition (CVPR), 2019 Wei-Chih Hung Varun Jampani Sifei Liu Pavlo Molchanov Ming-Hsuan Yang Jan Kautz 175 157 0 03 May 2019
Visualizing Deep Networks by Optimizing with Integrated Gradients Chen Ma Saeed Khorram Fuxin Li FAtt 150 138 0 02 May 2019
Multi-level Encoder-Decoder Architectures for Image Restoration Indra Deep Mastan Shanmuganathan Raman SupR 199 16 0 01 May 2019
Concise Fuzzy System Modeling Integrating Soft Subspace Clustering and Sparse Learning Peng Xu Zhaohong Deng Chen Cui Te Zhang K. Choi Suhang Gu Jun Wang Shitong Wang 91 34 0 24 Apr 2019
Understanding Neural Networks via Feature Visualization: A survey Anh Nguyen J. Yosinski Jeff Clune FAtt 190 173 0 18 Apr 2019
Summit: Scaling Deep Learning Interpretability by Visualizing Activation and Attribution Summarizations Fred Hohman Haekyu Park Caleb Robinson Duen Horng Chau FAtt 3DH HAI 281 226 0 04 Apr 2019
Interpreting Adversarial Examples by Activation Promotion and Suppression Kaidi Xu Sijia Liu Gaoyuan Zhang Mengshu Sun Pu Zhao Quanfu Fan Chuang Gan Xinyu Lin AAML FAtt 247 46 0 03 Apr 2019
Deep Residual Autoencoder for quality independent JPEG restoration Simone Zini Luigi Celona Raimondo Schettini 133 19 0 14 Mar 2019
Paradox in Deep Neural Networks: Similar yet Different while Different yet Similar A. Akbarinia K. Gegenfurtner DRL 78 5 0 12 Mar 2019
Learning Regularity in Skeleton Trajectories for Anomaly Detection in Videos Romero Morais Vuong Le T. Tran Budhaditya Saha M. Mansour Svetha Venkatesh 306 298 0 08 Mar 2019
Weakly Supervised Complementary Parts Models for Fine-Grained Image Classification from the Bottom Up Weifeng Ge Xiangru Lin Yizhou Yu 191 287 0 07 Mar 2019
Interpretable Deep Learning in Drug Discovery Kristina Preuer Günter Klambauer F. Rippmann Sepp Hochreiter Thomas Unterthiner 165 100 0 07 Mar 2019
Understanding and Visualizing Deep Visual Saliency Models Sen He Hamed R. Tavakoli Ali Borji Yang Mi N. Pugeault FAtt 190 47 0 06 Mar 2019
Neural Networks Trained on Natural Scenes Exhibit Gestalt Closure Been Kim Emily Reif Martin Wattenberg Samy Bengio Michael C. Mozer 146 33 0 04 Mar 2019
neuralRank: Searching and ranking ANN-based model repositories N. Desai Linsong Chu R. Ganti Sebastian Stein Mudhakar Srivatsa 70 0 0 02 Mar 2019
Aggregating explanation methods for stable and robust explainability Laura Rieger Lars Kai Hansen AAML FAtt 268 15 0 01 Mar 2019
Discovery of Natural Language Concepts in Individual Units of CNNs Seil Na Yo Joong Choe Dong-Hyun Lee Gunhee Kim MILM 112 25 0 18 Feb 2019
Semantically Interpretable and Controllable Filter Sets Mohit Prabhushankar Gukyeong Kwon Dogancan Temel G. Al-Regib 89 4 0 17 Feb 2019
Self-supervised Visual Feature Learning with Deep Neural Networks: A Survey Longlong Jing Yingli Tian SSL 396 1,892 0 16 Feb 2019
Manifestation of Image Contrast in Deep Networks A. Akbarinia K. Gegenfurtner 82 4 0 12 Feb 2019
Human-Centered Tools for Coping with Imperfect Algorithms during Medical Decision-Making Carrie J. Cai Emily Reif Narayan Hegde J. Hipp Been Kim ... Martin Wattenberg F. Viégas G. Corrado Martin C. Stumpe Michael Terry 194 431 0 08 Feb 2019
Towards Automatic Concept-based Explanations Amirata Ghorbani James Wexler James Zou Been Kim FAtt LRM 313 20 0 07 Feb 2019
Saliency Tubes: Visual Explanations for Spatio-Temporal Convolutions Alexandros Stergiou G. Kapidis Grigorios Kalliatakis C. Chrysoulas R. Veltkamp R. Poppe FAtt 157 50 0 04 Feb 2019
Depthwise Convolution is All You Need for Learning Multiple Visual Domains Yunhui Guo Yandong Li Rogerio Feris Liqiang Wang Tajana Simunic OOD 208 188 0 03 Feb 2019
On the Units of GANs (Extended Abstract) David Bau Jun-Yan Zhu Hendrik Strobelt Bolei Zhou J. Tenenbaum William T. Freeman Antonio Torralba 102 64 0 29 Jan 2019
On the (In)fidelity and Sensitivity for Explanations Chih-Kuan Yeh Cheng-Yu Hsieh A. Suggala David I. Inouye Pradeep Ravikumar FAtt 315 521 0 27 Jan 2019
Surrogate Supervision for Medical Image Analysis: Effective Deep Learning From Limited Quantities of Labeled Data Nima Tajbakhsh Yufei Hu Junli Cao Xingjian Yan Yi Xiao Yong Lu Jianming Liang Demetri Terzopoulos Xiaowei Ding 160 80 0 25 Jan 2019
Ablation Studies in Artificial Neural Networks Richard Meyes Melanie Lu Constantin Waubert de Puiseau Tobias Meisen 154 260 0 24 Jan 2019
Unsupervised Learning of Neural Networks to Explain Neural Networks (extended abstract) Quanshi Zhang Yu Yang Ying Nian Wu FAtt SSL 77 1 0 21 Jan 2019
Explaining Explanations to Society Leilani H. Gilpin Cecilia Testart Nathaniel Fruchter Julius Adebayo XAI 200 36 0 19 Jan 2019
Toward Explainable Fashion Recommendation Pongsate Tangseng Takayuki Okatani 145 33 0 15 Jan 2019
Low-Cost Transfer Learning of Face Tasks T. John Isha Dua V. Balasubramanian C. V. Jawahar CLIP CVBM VLM 110 0 0 09 Jan 2019
Interpretable CNNs for Object Classification Quanshi Zhang Xin Eric Wang Ying Nian Wu Huilin Zhou Song-Chun Zhu 140 62 0 08 Jan 2019
Explaining AlphaGo: Interpreting Contextual Effects in Neural Networks Zenan Ling Haotian Ma Yu Yang Robert C. Qiu Song-Chun Zhu Quanshi Zhang MILM 136 4 0 08 Jan 2019
Visualizing Deep Similarity Networks Abby Stylianou Richard Souvenir Robert Pless FAtt 237 56 0 02 Jan 2019
Deep Paper Gestalt Jia-Bin Huang CVBM 114 20 0 20 Dec 2018
Explanatory Graphs for CNNs Quanshi Zhang Xin Eric Wang Ruiming Cao Ying Nian Wu Feng Shi Song-Chun Zhu FAtt GNN 110 3 0 18 Dec 2018
Mining Interpretable AOG Representations from Convolutional Networks via Active Question Answering Quanshi Zhang Ruiming Cao Ying Nian Wu Song-Chun Zhu 119 14 0 18 Dec 2018
Explaining Neural Networks Semantically and Quantitatively Runjin Chen Hao Chen Ge Huang Jie Ren Quanshi Zhang FAtt 129 59 0 18 Dec 2018
Interactive Naming for Explaining Deep Neural Networks: A Formative Study M. Hamidi-Haines Chen Ma Alan Fern Fuxin Li Prasad Tadepalli FAtt HAI 133 11 0 18 Dec 2018
Not Using the Car to See the Sidewalk: Quantifying and Controlling the Effects of Context in Classification and Segmentation Rakshith Shetty Bernt Schiele Mario Fritz 198 87 0 17 Dec 2018
Exploiting Kernel Sparsity and Entropy for Interpretable CNN Compression Yuchao Li Shaohui Lin Baochang Zhang Jianzhuang Liu David Doermann Yongjian Wu Feiyue Huang Rongrong Ji 182 140 0 11 Dec 2018
Prior-Knowledge and Attention-based Meta-Learning for Few-Shot Learning Yunxiao Qin Weiguo Zhang Chenxu Zhao Zezheng Wang Xiangyu Zhu Guojun Qi Jingping Shi Zhen Lei 218 28 0 11 Dec 2018
Image Score: How to Select Useful Samples Simiao Zuo Jialin Wu FAtt 87 0 0 02 Dec 2018
Understanding and Improving Kernel Local Descriptors Arun Mukundan Giorgos Tolias Andrei Bursuc Edouard Grave Ondřej Chum 112 12 0 27 Nov 2018
Dataset Distillation Tongzhou Wang Jun-Yan Zhu Antonio Torralba Alexei A. Efros DD 284 328 0 27 Nov 2018
GAN Dissection: Visualizing and Understanding Generative Adversarial Networks David Bau Jun-Yan Zhu Hendrik Strobelt Bolei Zhou J. Tenenbaum William T. Freeman Antonio Torralba GAN 71 0 0 26 Nov 2018