Network Dissection: Quantifying Interpretability of Deep Visual Representations

19 April 2017

Antonio Torralba

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

50 / 787 papers shown

Title
An Overview of Computational Approaches for Interpretation Analysis Philipp Blandfort Jörn Hees D. Patton 53 2 0 09 Nov 2018
Semantic bottleneck for computer vision tasks Apostolos Modas Seyed-Mohsen Moosavi-Dezfooli P. Frossard 92 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 92 184 0 03 Nov 2018
Brand > Logo: Visual Analysis of Fashion Brands M. Kiapour Robinson Piramuthu 40 7 0 23 Oct 2018
Interpreting Layered Neural Networks via Hierarchical Modular Representation C. Watanabe 84 19 0 03 Oct 2018
Training Machine Learning Models by Regularizing their Explanations A. Ross FaML 63 0 0 29 Sep 2018
A theoretical framework for deep locally connected ReLU network Yuandong Tian PINN 64 10 0 28 Sep 2018
Faithful Multimodal Explanation for Visual Question Answering Jialin Wu Raymond J. Mooney 85 91 0 08 Sep 2018
XAI Beyond Classification: Interpretable Neural Clustering Xi Peng Yunfan Li Ivor W. Tsang Erik Cambria Jiancheng Lv Qiufeng Wang 75 75 0 22 Aug 2018
Unsupervised learning of foreground object detection Ioana Croitoru Simion-Vlad Bogolin Marius Leordeanu OCL 65 49 0 14 Aug 2018
Improving Shape Deformation in Unsupervised Image-to-Image Translation Aaron Gokaslan Vivek Ramanujan Daniel E. Ritchie K. Kim James Tompkin 118 76 0 13 Aug 2018
Out of the Black Box: Properties of deep neural networks and their applications Nizar Ouarti D. Carmona FAtt AAML 28 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 90 37 0 08 Aug 2018
Diverse Conditional Image Generation by Stochastic Regression with Latent Drop-Out Codes Yang He Bernt Schiele Mario Fritz SyDa 47 4 0 03 Aug 2018
Unified Perceptual Parsing for Scene Understanding Tete Xiao Yingcheng Liu Bolei Zhou Yuning Jiang Jian Sun OCL VOS 214 1,910 0 26 Jul 2018
Rethinking the Form of Latent States in Image Captioning Bo Dai Deming Ye Dahua Lin 78 18 0 26 Jul 2018
Explainable Neural Computation via Stack Neural Module Networks Ronghang Hu Jacob Andreas Trevor Darrell Kate Saenko LRM OCL 108 199 0 23 Jul 2018
Parallel Convolutional Networks for Image Recognition via a Discriminator Shiqi Yang G. Peng 26 3 0 06 Jul 2018
This Looks Like That: Deep Learning for Interpretable Image Recognition Chaofan Chen Oscar Li Chaofan Tao A. Barnett Jonathan Su Cynthia Rudin 335 1,193 0 27 Jun 2018
Deep Feature Factorization For Concept Discovery Edo Collins R. Achanta Sabine Süsstrunk 82 92 0 26 Jun 2018
The Neural Painter: Multi-Turn Image Generation Ryan Y. Benmalek Claire Cardie Serge J. Belongie Xiaodong He Jianfeng Gao MLLM 55 7 0 16 Jun 2018
Insights on representational similarity in neural networks with canonical correlation Ari S. Morcos M. Raghu Samy Bengio DRL 135 447 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 57 9 0 14 Jun 2018
Revisiting the Importance of Individual Units in CNNs via Ablation Bolei Zhou Yiyou Sun David Bau Antonio Torralba FAtt 132 117 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 13 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 144 1,874 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 71 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 63 7 0 29 May 2018
Semantic Network Interpretation Pei Guo Ryan Farrell MILM FAtt 34 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 72 27 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 93 84 0 15 May 2018
Disentangling Controllable and Uncontrollable Factors of Variation by Interacting with the World Yoshihide Sawada DRL 68 10 0 19 Apr 2018
Understanding Community Structure in Layered Neural Networks C. Watanabe Kaoru Hiramatsu K. Kashino 138 22 0 13 Apr 2018
Unsupervised Discovery of Object Landmarks as Structural Representations Y. Zhang Yijie Guo Yixin Jin Yijun Luo Zhiyuan He Honglak Lee OCL 102 194 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 110 154 0 08 Apr 2018
Quantitative Evaluation of Style Transfer Mao-Chuang Yeh Shuai Tang Anand Bhattad David A. Forsyth 73 14 0 31 Mar 2018
What Do We Understand About Convolutional Networks? Isma Hadji Richard P. Wildes FAtt 66 99 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 51 30 0 22 Mar 2018
On the importance of single directions for generalization Ari S. Morcos David Barrett Neil C. Rabinowitz M. Botvinick 124 333 0 19 Mar 2018
Learning Unsupervised Visual Grounding Through Semantic Self-Supervision Syed Ashar Javed Shreyas Saxena Vineet Gandhi SSL 76 25 0 17 Mar 2018
What Catches the Eye? Visualizing and Understanding Deep Saliency Models Sen He Ali Borji Yang Mi N. Pugeault FAtt 67 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 32 17 0 13 Mar 2018
Deep k-Nearest Neighbors: Towards Confident, Interpretable and Robust Deep Learning Nicolas Papernot Patrick McDaniel OOD AAML 156 508 0 13 Mar 2018
Deep Learning in Mobile and Wireless Networking: A Survey Chaoyun Zhang P. Patras Hamed Haddadi 134 1,320 0 12 Mar 2018
The Challenge of Crafting Intelligible Intelligence Daniel S. Weld Gagan Bansal 58 244 0 09 Mar 2018
Multi-Evidence Filtering and Fusion for Multi-Label Classification, Object Detection and Semantic Segmentation Based on Weakly Supervised Learning Weifeng Ge Sibei Yang Yizhou Yu 108 190 0 26 Feb 2018
Predicting Adversarial Examples with High Confidence A. Galloway Graham W. Taylor M. Moussa AAML 56 9 0 13 Feb 2018
Global Model Interpretation via Recursive Partitioning Chengliang Yang Anand Rangarajan Sanjay Ranka FAtt 65 81 0 11 Feb 2018
Pros and Cons of GAN Evaluation Measures Ali Borji ELM EGVM 96 884 0 09 Feb 2018
Intriguing Properties of Randomly Weighted Networks: Generalizing While Learning Next to Nothing Amir Rosenfeld John K. Tsotsos MLT 75 52 0 02 Feb 2018