Sparse coding with an overcomplete basis set: A strategy employed by V1?

[1]  Peter Földiák,et al.  SPARSE CODING IN THE PRIMATE CORTEX , 2002 .

[2]  Axthonv G. Oettinger,et al.  IEEE Transactions on Information Theory , 1998 .

[3]  Geoffrey E. Hinton,et al.  Generative models for discovering sparse distributed representations. , 1997, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[4]  Rajesh P. N. Rao,et al.  Dynamic Model of Visual Recognition Predicts Neural Response Properties in the Visual Cortex , 1997, Neural Computation.

[5]  George Francis Harpur,et al.  Low Entropy Coding with Unsupervised Neural Networks , 1997 .

[6]  Terrence J. Sejnowski,et al.  Bayesian Unsupervised Learning of Higher Order Structure , 1996, NIPS.

[7]  B. Olshausen.  Learning linear, sparse, factorial codes , 1996 .

[8]  Roland Baddeley,et al.  An efficient code in V1? , 1996, Nature.

[9]  David J. Field,et al.  Emergence of simple-cell receptive field properties by learning a sparse code for natural images , 1996, Nature.

[10]  R C Reid,et al.  Efficient Coding of Natural Scenes in the Lateral Geniculate Nucleus: Experimental Test of a Computational Theory , 1996, The Journal of Neuroscience.

[11]  D. Field,et al.  Natural image statistics and efficient coding. , 1996, Network.

[12]  R W Prager,et al.  Development of low entropy coding in a recurrent network. , 1996, Network.

[13]  D. Field,et al.  Natural Image Statistics and Eecient Coding , 1996 .

[14]  Barak A. Pearlmutter,et al.  A Context-Sensitive Generalization of ICA , 1996 .

[15]  Andrzej Cichocki,et al.  A New Learning Algorithm for Blind Signal Separation , 1995, NIPS.

[16]  Terrence J. Sejnowski,et al.  An Information-Maximization Approach to Blind Separation and Blind Deconvolution , 1995, Neural Computation.

[17]  Geoffrey E. Hinton,et al.  The Helmholtz Machine , 1995, Neural Computation.

[18]  Eric Saund,et al.  A Multiple Cause Mixture Model for Unsupervised Learning , 1995, Neural Computation.

[19]  Bruno A. Olshausen,et al.  A Model of the Spatial-Frequency Organization in Primate Striate Cortex , 1995 .

[20]  James M. Bower,et al.  The Neurobiology of Computation , 1995, Springer US.

[21]  C. Fyfe,et al.  Finding compact and sparse-distributed representations of visual images , 1995 .

[22]  J. Atick,et al.  Temporal decorrelation: a theory of lagged and nonlagged responses in the lateral geniculate nucleus , 1995 .

[23]  Michael A. Arbib,et al.  The handbook of brain theory and neural networks , 1995, A Bradford book.

[24]  S. Klinke,et al.  Exploratory Projection Pursuit , 1995 .

[25]  David Mumford,et al.  Neuronal Architectures for Pattern-theoretic Problems , 1995 .

[26]  C. C. Law,et al.  Formation of receptive fields in realistic visual environments according to the Bienenstock, Cooper, and Munro (BCM) theory. , 1994, Proceedings of the National Academy of Sciences of the United States of America.

[27]  David J. Field,et al.  What Is the Goal of Sensory Coding? , 1994, Neural Computation.

[28]  Pierre Comon,et al.  Independent component analysis, A new concept? , 1994, Signal Process..

[29]  Joel L. Davis,et al.  Large-Scale Neuronal Theories of the Brain , 1994 .

[30]  R. Zemel.  A minimum description length framework for unsupervised learning , 1994 .

[31]  Edward H. Adelson,et al.  Shiftable multiscale transforms , 1992, IEEE Trans. Inf. Theory.

[32]  Joseph J. Atick,et al.  What Does the Retina Know about Natural Scenes? , 1992, Neural Computation.

[33]  Nathan Intrator,et al.  Feature Extraction Using an Unsupervised Neural Network , 1992, Neural Computation.

[34]  Joseph J. Atick,et al.  Towards a Theory of Early Visual Processing , 1990, Neural Computation.

[35]  D. Tolhurst,et al.  The effect of threshold on the relationship between the receptive-field profile and the spatial-frequency tuning cure in simple cells of the cat's striate cortex , 1989, Visual Neuroscience.

[36]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[37]  J.G. Daugman,et al.  Entropy reduction and decorrelation in visual coding by oriented neural receptive fields , 1989, IEEE Transactions on Biomedical Engineering.

[38]  M. V. Rossum,et al.  In Neural Computation , 2022 .

[39]  A. Parker,et al.  Two-dimensional spatial structure of receptive fields in monkey striate cortex. , 1988, Journal of the Optical Society of America. A, Optics and image science.

[40]  D J Field,et al.  Relations between the statistics of natural images and the response properties of cortical cells. , 1987, Journal of the Optical Society of America. A, Optics and image science.

[41]  RussLL L. Ds Vnlos,et al.  SPATIAL FREQUENCY SELECTIVITY OF CELLS IN MACAQUE VISUAL CORTEX , 2022 .

[42]  G. Sperling.  MBS 96-15 Independence Rejection: An Unsupervised Learning Algorithm for Extracting Latent Source Structures from Arbitrary Image Populations , 2022 .