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Understanding trained CNNs by indexing neuron selectivity

1 February 2017

Papers citing "Understanding trained CNNs by indexing neuron selectivity"

25 / 25 papers shown

Title
Revisiting the Importance of Individual Units in CNNs via Ablation Bolei Zhou Yiyou Sun David Bau Antonio Torralba FAtt 101 117 0 07 Jun 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 47 24 0 31 May 2018
Net2Vec: Quantifying and Explaining how Concepts are Encoded by Filters in Deep Neural Networks Ruth C. Fong Andrea Vedaldi FAtt 71 264 0 10 Jan 2018
Distilling a Neural Network Into a Soft Decision Tree Nicholas Frosst Geoffrey E. Hinton 411 638 0 27 Nov 2017
Interpreting Deep Visual Representations via Network Dissection Bolei Zhou David Bau A. Oliva Antonio Torralba FAtt MILM 58 324 0 15 Nov 2017
Xception: Deep Learning with Depthwise Separable Convolutions François Chollet MDE BDL PINN 1.4K 14,596 0 07 Oct 2016
The Latin American Giant Observatory: a successful collaboration in Latin America based on Cosmic Rays and computer science domains Hernán Asorey R. Mayo-García L. Núñez M. Pascual A. J. Rubio-Montero M. Suárez-Durán L. A. Torres-Niño 89 5 0 30 May 2016
Multifaceted Feature Visualization: Uncovering the Different Types of Features Learned By Each Neuron in Deep Neural Networks Anh Totti Nguyen J. Yosinski Jeff Clune 70 329 0 11 Feb 2016
Convergent Learning: Do different neural networks learn the same representations? Yixuan Li J. Yosinski Jeff Clune Hod Lipson John E. Hopcroft SSL 86 371 0 24 Nov 2015
Understanding Neural Networks Through Deep Visualization J. Yosinski Jeff Clune Anh Totti Nguyen Thomas J. Fuchs Hod Lipson FAtt AI4CE 124 1,874 0 22 Jun 2015
Inverting Visual Representations with Convolutional Networks Alexey Dosovitskiy Thomas Brox SSL FAtt 68 666 0 09 Jun 2015
Understanding deep features with computer-generated imagery Mathieu Aubry Bryan C. Russell 85 149 0 03 Jun 2015
Striving for Simplicity: The All Convolutional Net Jost Tobias Springenberg Alexey Dosovitskiy Thomas Brox Martin Riedmiller FAtt 248 4,681 0 21 Dec 2014
Why does Deep Learning work? - A perspective from Group Theory Arnab Paul Suresh Venkatasubramanian 60 21 0 20 Dec 2014
Explaining and Harnessing Adversarial Examples Ian Goodfellow Jonathon Shlens Christian Szegedy AAML GAN 280 19,107 0 20 Dec 2014
MatConvNet - Convolutional Neural Networks for MATLAB Andrea Vedaldi Karel Lenc 322 2,948 0 15 Dec 2014
Understanding Deep Image Representations by Inverting Them Aravindh Mahendran Andrea Vedaldi FAtt 126 1,965 0 26 Nov 2014
Learning to Generate Chairs, Tables and Cars with Convolutional Networks Alexey Dosovitskiy Jost Tobias Springenberg Maxim Tatarchenko Thomas Brox GAN 176 676 0 21 Nov 2014
Very Deep Convolutional Networks for Large-Scale Image Recognition Karen Simonyan Andrew Zisserman FAtt MDE 1.7K 100,479 0 04 Sep 2014
Deep Neural Networks Rival the Representation of Primate IT Cortex for Core Visual Object Recognition C. Cadieu Ha Hong Daniel L. K. Yamins Nicolas Pinto Diego Ardila E. Solomon N. Majaj J. DiCarlo 94 787 0 12 Jun 2014
Return of the Devil in the Details: Delving Deep into Convolutional Nets Ken Chatfield Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 221 3,418 0 14 May 2014
Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps Karen Simonyan Andrea Vedaldi Andrew Zisserman FAtt 312 7,308 0 20 Dec 2013
Visualizing and Understanding Convolutional Networks Matthew D. Zeiler Rob Fergus FAtt SSL 595 15,893 0 12 Nov 2013
Rich feature hierarchies for accurate object detection and semantic segmentation Ross B. Girshick Jeff Donahue Trevor Darrell Jitendra Malik ObjD 289 26,211 0 11 Nov 2013
Provable Bounds for Learning Some Deep Representations Sanjeev Arora Aditya Bhaskara Rong Ge Tengyu Ma BDL 97 335 0 23 Oct 2013