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Layer-wise relevance propagation is a framework which allows to decompose the prediction of a deep neural network computed over a sample, e.g.
Visual categorization with bags of keypoints
Gabriela Csurka, Christopher R. Dance, Lixin Fan, Jutta Willamowski, and Cédric Bray · 2004
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Learning multiple layers of features from tiny images
Alex Krizhevsky · 2009
Earlier work this paper cites.
Evaluating color descriptors for object and scene recognition
Koen E. A. van de Sande, Theo Gevers, and Cees G. M. Snoek · 2010
Earlier work this paper cites.
Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton · 2012
Earlier work this paper cites.
Deep inside convolutional networks: Visualising image classification models and saliency maps
Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman · 2013
Cited alongside, same era.
Visualizing and understanding convolutional networks
Matthew D. Zeiler and Rob Fergus · 2014
Cited alongside, same era.
Learning deep features for scene recognition using places database
Bolei Zhou, Agata Lapedriza, Jianxiong Xiao, Antonio Torralba, and Aude Oliva · 2014
Cited alongside, same era.
On pixel-wise explanations for non-linear classifier decisions by layer-wise relevance propagation
Sebastian Bach, Alexander Binder, Grégoire Montavon, Frederick Klauschen, Klaus-Robert Müller, and Wojciech Samek · 2015
Cited alongside, same era.
Explaining nonlinear classification decisions with deep taylor decomposition
Grégoire Montavon, Sebastian Bach, Alexander Binder, Wojciech Samek, and Klaus-Robert Müller · 2015
Later among the works it cites.
ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei · 2015
Later among the works it cites.
Evaluating the visualization of what a deep neural network has learned
Wojciech Samek, Alexander Binder, Grégoire Montavon, Sebastian Bach, and Klaus-Robert Müller · 2015
Later among the works it cites.
Analyzing classifiers: Fisher vectors and deep neural networks
Sebastian Bach, Alexander Binder, Grégoire Montavon, Frederick Klauschen, Klaus-Robert Müller, and Wojciech Samek · 2016
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