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
SpotTune: Transfer Learning through Adaptive Fine-tuningComputer Vision and Pattern Recognition (CVPR), 2018 Yunhui Guo Humphrey Shi Abhishek Kumar Kristen Grauman Tajana Simunic Rogerio Feris 282 485 0 21 Nov 2018
How far from automatically interpreting deep learning Jinwei Zhao Qizhou Wang Yufei Wang Xinhong Hei Yu Liu 68 1 0 19 Nov 2018
Representation based and Attention augmented Meta learning Yunxiao Qin Chenxu Zhao Zezheng Wang Junliang Xing Jun Wan Zhen Lei 179 1 0 19 Nov 2018
Understanding Learned Models by Identifying Important Features at the Right ResolutionAAAI Conference on Artificial Intelligence (AAAI), 2018 Kyubin Lee Akshay Sood M. Craven 147 8 0 18 Nov 2018
CIFAR10 to Compare Visual Recognition Performance between Deep Neural Networks and Humans T. Ho-Phuoc 122 46 0 18 Nov 2018
An Overview of Computational Approaches for Interpretation Analysis Philipp Blandfort Jörn Hees D. Patton 192 2 0 09 Nov 2018
Semantic bottleneck for computer vision tasksAsian Conference on Computer Vision (ACCV), 2018 Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard 145 17 0 06 Nov 2018
Identifying and Controlling Important Neurons in Neural Machine Translation A. Bau Yonatan Belinkov Hassan Sajjad Nadir Durrani Fahim Dalvi James R. Glass MILM 202 190 0 03 Nov 2018
Brand > Logo: Visual Analysis of Fashion Brands M. Kiapour Robinson Piramuthu 118 7 0 23 Oct 2018
Interpreting Layered Neural Networks via Hierarchical Modular Representation C. Watanabe 141 20 0 03 Oct 2018
Training Machine Learning Models by Regularizing their Explanations A. Ross FaML 109 0 0 29 Sep 2018
A theoretical framework for deep locally connected ReLU network Yuandong Tian PINN 97 10 0 28 Sep 2018
Faithful Multimodal Explanation for Visual Question Answering Jialin Wu Raymond J. Mooney 178 97 0 08 Sep 2018
XAI Beyond Classification: Interpretable Neural Clustering Xi Peng Yunfan Li Ivor W. Tsang Erik Cambria Jiancheng Lv Qiufeng Wang 166 83 0 22 Aug 2018
Unsupervised learning of foreground object detection Ioana Croitoru Simion-Vlad Bogolin Marius Leordeanu OCL 193 52 0 14 Aug 2018
Improving Shape Deformation in Unsupervised Image-to-Image Translation Aaron Gokaslan Vivek Ramanujan Daniel E. Ritchie K. Kim James Tompkin 179 77 0 13 Aug 2018
Out of the Black Box: Properties of deep neural networks and their applications Nizar Ouarti D. Carmona FAtt AAML 90 3 0 10 Aug 2018
Choose Your Neuron: Incorporating Domain Knowledge through Neuron-Importance Ramprasaath R. Selvaraju Prithvijit Chattopadhyay Mohamed Elhoseiny Tilak Sharma Dhruv Batra Devi Parikh Stefan Lee 159 37 0 08 Aug 2018
Diverse Conditional Image Generation by Stochastic Regression with Latent Drop-Out Codes Yang He Bernt Schiele Mario Fritz SyDa 95 4 0 03 Aug 2018
Unified Perceptual Parsing for Scene Understanding Tete Xiao Yingcheng Liu Bolei Zhou Yuning Jiang Jian Sun OCL VOS 390 2,237 0 26 Jul 2018
Rethinking the Form of Latent States in Image Captioning Bo Dai Deming Ye Dahua Lin 116 22 0 26 Jul 2018
Explainable Neural Computation via Stack Neural Module Networks Ronghang Hu Jacob Andreas Trevor Darrell Kate Saenko LRM OCL 315 204 0 23 Jul 2018
Parallel Convolutional Networks for Image Recognition via a DiscriminatorAsian Conference on Computer Vision (ACCV), 2017 Shiqi Yang G. Peng 113 3 0 06 Jul 2018
This Looks Like That: Deep Learning for Interpretable Image RecognitionNeural Information Processing Systems (NeurIPS), 2018 Chaofan Chen Oscar Li Chaofan Tao A. Barnett Jonathan Su Cynthia Rudin 606 1,372 0 27 Jun 2018
Deep Feature Factorization For Concept DiscoveryEuropean Conference on Computer Vision (ECCV), 2018 Edo Collins R. Achanta Sabine Süsstrunk 456 107 0 26 Jun 2018
The Neural Painter: Multi-Turn Image Generation Ryan Y. Benmalek Claire Cardie Serge J. Belongie Xiaodong He Jianfeng Gao MLLM 147 7 0 16 Jun 2018
Insights on representational similarity in neural networks with canonical correlation Ari S. Morcos M. Raghu Samy Bengio DRL 353 482 0 14 Jun 2018
Scrutinizing and De-Biasing Intuitive Physics with Neural Stethoscopes F. Fuchs Oliver Groth Adam R. Kosiorek Alex Bewley Markus Wulfmeier Andrea Vedaldi Ingmar Posner 209 9 0 14 Jun 2018
Revisiting the Importance of Individual Units in CNNs via Ablation Bolei Zhou Yiyou Sun David Bau Antonio Torralba FAtt 228 125 0 07 Jun 2018
A Peek Into the Hidden Layers of a Convolutional Neural Network Through a Factorization Lens Uday Singh Saini Evangelos E. Papalexakis FAtt 49 2 0 06 Jun 2018
Explaining Explanations: An Overview of Interpretability of Machine Learning Leilani H. Gilpin David Bau Ben Z. Yuan Ayesha Bajwa Michael A. Specter Lalana Kagal XAI 977 2,088 0 31 May 2018
DeepMiner: Discovering Interpretable Representations for Mammogram Classification and Explanation Jimmy Wu Bolei Zhou D. Peck S. Hsieh V. Dialani Lester W. Mackey Genevieve Patterson FAtt MedIm 164 24 0 31 May 2018
Teaching Meaningful Explanations Noel Codella Michael Hind Karthikeyan N. Ramamurthy Murray Campbell Amit Dhurandhar Kush R. Varshney Dennis L. Wei Aleksandra Mojsilović FAtt XAI 190 7 0 29 May 2018
Semantic Network Interpretation Pei Guo Ryan Farrell MILM FAtt 125 0 0 23 May 2018
Unsupervised Learning of Neural Networks to Explain Neural Networks Quanshi Zhang Yu Yang Yuchen Liu Ying Nian Wu Song-Chun Zhu FAtt SSL 147 28 0 18 May 2018
On Learning Associations of Faces and Voices Changil Kim Hijung Valentina Shin Tae-Hyun Oh Alexandre Kaspar Mohamed A. Elgharib Wojciech Matusik CVBM 210 91 0 15 May 2018
Disentangling Controllable and Uncontrollable Factors of Variation by Interacting with the World Yoshihide Sawada DRL 167 10 0 19 Apr 2018
Understanding Community Structure in Layered Neural Networks C. Watanabe Kaoru Hiramatsu K. Kashino 201 22 0 13 Apr 2018
Unsupervised Discovery of Object Landmarks as Structural Representations Xicheng Zhang Yijie Guo Yixin Jin Yijun Luo Zhiyuan He Honglak Lee OCL 240 206 0 12 Apr 2018
Learning-based Video Motion Magnification Tae-Hyun Oh Ronnachai Jaroensri Changil Kim Mohamed A. Elgharib F. Durand William T. Freeman Wojciech Matusik 202 177 0 08 Apr 2018
Quantitative Evaluation of Style Transfer Mao-Chuang Yeh Shuai Tang Anand Bhattad David A. Forsyth 159 14 0 31 Mar 2018
What Do We Understand About Convolutional Networks? Isma Hadji Richard P. Wildes FAtt 130 104 0 23 Mar 2018
What do Deep Networks Like to See? Sebastián M. Palacio Joachim Folz Jörn Hees Federico Raue Damian Borth Andreas Dengel SSL 77 30 0 22 Mar 2018
On the importance of single directions for generalization Ari S. Morcos David Barrett Neil C. Rabinowitz M. Botvinick 398 347 0 19 Mar 2018
Learning Unsupervised Visual Grounding Through Semantic Self-Supervision Syed Ashar Javed Shreyas Saxena Vineet Gandhi SSL 184 25 0 17 Mar 2018
What Catches the Eye? Visualizing and Understanding Deep Saliency Models Sen He Ali Borji Yang Mi N. Pugeault FAtt 155 12 0 15 Mar 2018
Expert identification of visual primitives used by CNNs during mammogram classification Jimmy Wu D. Peck S. Hsieh V. Dialani C. Lehman Bolei Zhou Vasilis Syrgkanis Lester W. Mackey Genevieve Patterson 73 17 0 13 Mar 2018
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning Nicolas Papernot Patrick McDaniel OOD AAML 320 545 0 13 Mar 2018
Deep Learning in Mobile and Wireless Networking: A SurveyIEEE Communications Surveys and Tutorials (COMST), 2018 Chaoyun Zhang P. Patras Hamed Haddadi 346 1,409 0 12 Mar 2018
The Challenge of Crafting Intelligible Intelligence Daniel S. Weld Gagan Bansal 152 252 0 09 Mar 2018