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We develop a new statistical model for photographic images, in which the local responses of a bank of linear filters are described as jointly Gaussian, with zero mean and a covariance that varies slowly over spatial position.
The statistics of natural images
Ruderman, Daniel L · 1994
Earlier work this paper cites.
Emergence of simple-cell receptive field properties by learning a sparse code for natural images
Olshausen, Bruno A. and Field, David J · 1996
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The ‘independent components’ of natural scenes are edge filters
Bell, Anthony J. and Sejnowski, Terrence J · 1997
Earlier work this paper cites.
Statistical models for images: Compression, restoration and synthesis
Simoncelli, Eero P · 1997
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Independent component filters of natural images compared with simple cells in primary visual cortex
van Hateren, J. H. and van der Schaaf, A · 1998
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Hierarchical models of object recognition in cortex
Riesenhuber, Maximilian and Poggio, Tomaso · 1999
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The atoms of vision: Cartesian or polar?
Zetzsche, C. and Krieger, G · 1999
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Emergence of Phase- and Shift-Invariant Features by Decomposition of Natural Images into Independent Feature Subspaces
Hyvärinen, Aapo and Hoyer, Patrik · 2000
Cited alongside, same era.
A Parametric Texture Model Based on Joint Statistics of Complex Wavelet Coefficients
Portilla, Javier and Simoncelli, Eero P · 2000
Cited alongside, same era.
Scale mixtures of Gaussians and the statistics of natural images
Wainwright, Martin J. and Simoncelli, Eero P · 2000
Cited alongside, same era.
A Hierarchical Bayesian Model for Learning Nonlinear Statistical Regularities in Nonstationary Natural Signals
Karklin, Yan and Lewicki, Michael S · 2005
Cited alongside, same era.
For most large underdetermined systems of equations, the minimal l 1 l_{1} -norm near-solution approximates the sparsest near-solution
Donoho, David · 2006
Cited alongside, same era.
Emergence of complex cell properties by learning to generalize in natural scenes
Karklin, Yan and Lewicki, Michael S · 2009
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Nonlinear extraction of ‘independent components’ of natural images using radial Gaussianization
Lyu, Siwei and Simoncelli, Eero P · 2009
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Torch7: A matlab-like environment for machine learning
Collobert, Ronan, Kavukcuoglu, Koray, and Farabet, Clément · 2011
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Recovery of sparse translation-invariant signals with continuous basis pursuit
Ekanadham, Chaitanya, Tranchina, Daniel, and Simoncelli, Eero P · 2011
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Invariant Scattering Convolution Networks
Bruna, Joan and Mallat, Stéphane · 2012
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Signal Recovery from Pooling Representations
Bruna, Joan, Szlam, Arthur, and LeCun, Yann · 2013
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Image denoising using mixtures of Gaussian scale mixtures
Guerrero-Colón, Jose A., Simoncelli, Eero P., and Portilla, Javier · 2008
Cited alongside, same era.
What is the best multi-stage architecture for object recognition?
Jarrett, Kevin, Kavukcuoglu, Koray, Ranzato, Marc’Aurelio, and LeCun, Yann · 2009
Cited alongside, same era.
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Analysis K-SVD: a dictionary-learning algorithm for the analysis sparse model
Rubinstein, Ron, Peleg, Tomer, and Elad, Michael · 2013
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