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
Multi-level Encoder-Decoder Architectures for Image Restoration Indra Deep Mastan Shanmuganathan Raman SupR 67 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 54 32 0 24 Apr 2019
Understanding Neural Networks via Feature Visualization: A survey Anh Nguyen J. Yosinski Jeff Clune FAtt 86 163 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 102 218 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 147 43 0 03 Apr 2019
Deep Residual Autoencoder for quality independent JPEG restoration Simone Zini Simone Bianco Raimondo Schettini 80 18 0 14 Mar 2019
Paradox in Deep Neural Networks: Similar yet Different while Different yet Similar A. Akbarinia K. Gegenfurtner DRL 40 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 179 263 0 08 Mar 2019
Weakly Supervised Complementary Parts Models for Fine-Grained Image Classification from the Bottom Up Weifeng Ge Xiangru Lin Yizhou Yu 107 257 0 07 Mar 2019
Interpretable Deep Learning in Drug Discovery Kristina Preuer Günter Klambauer F. Rippmann Sepp Hochreiter Thomas Unterthiner 83 89 0 07 Mar 2019
Understanding and Visualizing Deep Visual Saliency Models Sen He Hamed R. Tavakoli Ali Borji Yang Mi N. Pugeault FAtt 71 46 0 06 Mar 2019
Neural Networks Trained on Natural Scenes Exhibit Gestalt Closure Been Kim Emily Reif Martin Wattenberg Samy Bengio Michael C. Mozer 87 31 0 04 Mar 2019
neuralRank: Searching and ranking ANN-based model repositories N. Desai Linsong Chu R. Ganti Sebastian Stein Mudhakar Srivatsa 11 0 0 02 Mar 2019
Aggregating explanation methods for stable and robust explainability Laura Rieger Lars Kai Hansen AAML FAtt 57 12 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 55 24 0 18 Feb 2019
Semantically Interpretable and Controllable Filter Sets Mohit Prabhushankar Gukyeong Kwon Dogancan Temel G. Al-Regib 52 4 0 17 Feb 2019
Self-supervised Visual Feature Learning with Deep Neural Networks: A Survey Longlong Jing Yingli Tian SSL 247 1,707 0 16 Feb 2019
Manifestation of Image Contrast in Deep Networks A. Akbarinia K. Gegenfurtner 33 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 137 407 0 08 Feb 2019
Towards Automatic Concept-based Explanations Amirata Ghorbani James Wexler James Zou Been Kim FAtt LRM 99 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 69 47 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 100 159 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 61 61 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 110 456 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 76 77 0 25 Jan 2019
Ablation Studies in Artificial Neural Networks Richard Meyes Melanie Lu Constantin Waubert de Puiseau Tobias Meisen 69 218 0 24 Jan 2019
Unsupervised Learning of Neural Networks to Explain Neural Networks (extended abstract) Quanshi Zhang Yu Yang Ying Nian Wu FAtt SSL 33 1 0 21 Jan 2019
Explaining Explanations to Society Leilani H. Gilpin Cecilia Testart Nathaniel Fruchter Julius Adebayo XAI 118 35 0 19 Jan 2019
Toward Explainable Fashion Recommendation Pongsate Tangseng Takayuki Okatani 59 29 0 15 Jan 2019
Low-Cost Transfer Learning of Face Tasks T. John Isha Dua V. Balasubramanian C. V. Jawahar CLIP CVBM VLM 44 0 0 09 Jan 2019
Interpretable CNNs for Object Classification Quanshi Zhang Xin Eric Wang Ying Nian Wu Huilin Zhou Song-Chun Zhu 61 54 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 43 3 0 08 Jan 2019
Visualizing Deep Similarity Networks Abby Stylianou Richard Souvenir Robert Pless FAtt 76 56 0 02 Jan 2019
Deep Paper Gestalt Jia-Bin Huang CVBM 50 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 44 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 58 14 0 18 Dec 2018
Explaining Neural Networks Semantically and Quantitatively Runjin Chen Hao Chen Ge Huang Jie Ren Quanshi Zhang FAtt 62 56 0 18 Dec 2018
Interactive Naming for Explaining Deep Neural Networks: A Formative Study M. Hamidi-Haines Zhongang Qi Alan Fern Fuxin Li Prasad Tadepalli FAtt HAI 50 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 95 83 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 82 130 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 74 24 0 11 Dec 2018
Image Score: How to Select Useful Samples Simiao Zuo Jialin Wu FAtt 22 0 0 02 Dec 2018
Understanding and Improving Kernel Local Descriptors Arun Mukundan Giorgos Tolias Andrei Bursuc Hervé Jégou Ondřej Chum 51 11 0 27 Nov 2018
Dataset Distillation Tongzhou Wang Jun-Yan Zhu Antonio Torralba Alexei A. Efros DD 121 297 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 31 0 0 26 Nov 2018
SpotTune: Transfer Learning through Adaptive Fine-tuning Yunhui Guo Humphrey Shi Abhishek Kumar Kristen Grauman Tajana Simunic Rogerio Feris 114 455 0 21 Nov 2018
How far from automatically interpreting deep learning Jinwei Zhao Qizhou Wang Yufei Wang Xinhong Hei Yu Liu 16 1 0 19 Nov 2018
Representation based and Attention augmented Meta learning Yunxiao Qin Chenxu Zhao Zezheng Wang Junliang Xing Jun Wan Zhen Lei 37 1 0 19 Nov 2018
Understanding Learned Models by Identifying Important Features at the Right Resolution Kyubin Lee Akshay Sood M. Craven 67 8 0 18 Nov 2018
CIFAR10 to Compare Visual Recognition Performance between Deep Neural Networks and Humans T. Ho-Phuoc 65 42 0 18 Nov 2018