ATTNEAVE F. (1954). Some informational aspects of visual perception. Psychological review. 61 [PubMed]

Anderson JR, Peterson C. (1987). A mean field theory learning algorithm for neural networks Complex Systems. 1

Apolloni B, Bertoni A, Campadelli P, de Falco D. (1991). Asymmetric Boltzmann machines. Biological cybernetics. 66 [PubMed]

Barber D, Sollich P. (2000). Gaussian fields for approximate inference in layered sigmoid belief networks Advances in neural information processing systems. 12

Barlow HB. (1959). The mechanisation of thought processes.

Bertsekas DP. (1995). Dynamic programming and optimal control.

Brook D. (1964). On the distinction between the conditional probability and the joint probability approaches in the specification of nearest-neighbor systems Biometrika. 51

Callaway EM. (2004). Feedforward, feedback and inhibitory connections in primate visual cortex. Neural networks : the official journal of the International Neural Network Society. 17 [PubMed]

Chengxiang Z, Dasgupta C, Singh MP. (2000). Retrieval properties of a Hopfield model with random asymmetric interactions. Neural computation. 12 [PubMed]

Cover TM, Thomas JA. (1991). Elements of Information Theory.

Crisanti A, Sompolinsky H. (1988). Dynamics of spin systems with randomly asymmetric bonds: Ising spins and Glauber dynamics. Physical review. A, General physics. 37 [PubMed]

Ejima Y et al. (2003). Interindividual and interspecies variations of the extrastriate visual cortex. Neuroreport. 14 [PubMed]

Felleman DJ, Van Essen DC. (1991). Distributed hierarchical processing in the primate cerebral cortex. Cerebral cortex (New York, N.Y. : 1991). 1 [PubMed]

Fergus R, Perona P, Zisserman A. (2007). Weakly supervised scale-invariant learning of models for visual recognition Intl J Comput Vis. 71

Field DJ. (1994). What is the goal of sensory coding? Neural Comput. 6

Foldiak P. (1991). Learning invariance from transformation sequences Neural Comput. 3

Fukushima K. (2005). Restoring partly occluded patterns: a neural network model. Neural networks : the official journal of the International Neural Network Society. 18 [PubMed]

Fukushima K, Miyake S. (1982). Neocognitron: A new algorithm for pattern recognition tolerant of deformations and shifts in position Pattern Recognition. 15

Galland CC. (1993). The limitations of deterministic Boltzmann machine learning Network. 4

Geman S, Geman D. (1984). Stochastic relaxation, gibbs distributions, and the bayesian restoration of images. IEEE transactions on pattern analysis and machine intelligence. 6 [PubMed]

Ghahramani Z, Jordan MI, Jaakkola TS, Saul LK. (1998). Learning in graphical models.

Gill J. (2001). Generalized linear models: A unified approach.

Grossberg S. (1976). Adaptive pattern classification and universal recoding: II. Feedback, expectation, olfaction, illusions. Biological cybernetics. 23 [PubMed]

Gutfreund H. (1990). Neural networks and spin glasses.

HUBEL DH, WIESEL TN. (1959). Receptive fields of single neurones in the cat's striate cortex. The Journal of physiology. 148 [PubMed]

Hawkins J, Blakeslee S. (2004). On Intelligence.

Hecht-nielsen R. (1998). A theory of cerebral cortex Proc. 1998 Int. Conf. Neural Information Processing, ICONIP98.

Hertz J, Krogh A, Palmer RG. (1991). Introduction to the Theory of Neural Computation..

Hinton G, Teh Y, Welling M, Osindero S. (2003). Energy-based models for sparse overcomplete representations Journal Of Machine Learning Res [special Issue]. 4

Hinton GE, Ghahramani Z. (1997). Generative models for discovering sparse distributed representations. Philosophical transactions of the Royal Society of London. Series B, Biological sciences. 352 [PubMed]

Hinton GE, Osindero S, Teh YW. (2006). A fast learning algorithm for deep belief nets. Neural computation. 18 [PubMed]

Hinton GE, Salakhutdinov RR. (2006). Reducing the dimensionality of data with neural networks. Science (New York, N.Y.). 313 [PubMed]

Hinton GE, Teh Y. (2001). Rate-coded restricted Boltzmann machines for face recognition Advances in neural information processing systems. 13

Hopfield JJ. (1982). Neural networks and physical systems with emergent collective computational abilities. Proceedings of the National Academy of Sciences of the United States of America. 79 [PubMed]

Hoyer PO, Hyvärinen A. (2002). A multi-layer sparse coding network learns contour coding from natural images. Vision research. 42 [PubMed]

Johnson O. (2004). Information theory and the central limit theorem.

Jordan MI, Saul LK. (1998). Learning in graphical models.

Kandel ER, Jessell TM, Schwartz JH. (2000). Principles of neural science (4th ed).

Kappen HJ, Spanjers JJ. (2000). Mean field theory for asymmetric neural networks. Physical review. E, Statistical physics, plasmas, fluids, and related interdisciplinary topics. 61 [PubMed]

Kay SM. (1993). Fundamentals of Statistical Signal Processing: Estimation Theory.

Kosslyn SM, Thompson WL, Alpert NM. (1997). Neural systems shared by visual imagery and visual perception: a positron emission tomography study. NeuroImage. 6 [PubMed]

Kreiman G, Koch C, Fried I. (2000). Category-specific visual responses of single neurons in the human medial temporal lobe. Nature neuroscience. 3 [PubMed]

Kreutz-Delgado K, Murray JF. (2001). An improved FOCUSS-based learning algorithm for solving sparse linear inverse problems Conference Record of the 35th Asilomar Conference on Signals, Systems and Computers. 1

Kreutz-Delgado K, Murray JF. (2006). Learning sparse overcomplete codes for images J VLSI Signal Process. 45

Kreutz-Delgado K et al. (2003). Dictionary learning algorithms for sparse representation. Neural computation. 15 [PubMed]

Lee TS, Mumford D. (2003). Hierarchical Bayesian inference in the visual cortex. Journal of the Optical Society of America. A, Optics, image science, and vision. 20 [PubMed]

Lee TS, Mumford D, Romero R, Lamme VA. (1998). The role of the primary visual cortex in higher level vision. Vision research. 38 [PubMed]

Lewicki MS, Sejnowski TJ. (2000). Learning overcomplete representations. Neural computation. 12 [PubMed]

Mountcastle VB. (1978). An organizing principle for cerebral function The mindful brain.

Murray JF. (2005). Visual recognition, inference and coding using learned sparse overcomplete representations Unpublished doctoral dissertation, University of California, San Diego.

Olshausen BA, Field DJ. (1996). Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature. 381 [PubMed]

Olshausen BA, Field DJ. (1997). Sparse coding with an overcomplete basis set: a strategy employed by V1? Vision research. 37 [PubMed]

Olshausen BA, Field DJ. (2005). 23 problems in systems neuroscience.

Parisi G. (1986). A symmetric neural networks and the process of learning J Phys A Math Gen. 19

Quiroga RQ, Reddy L, Kreiman G, Koch C, Fried I. (2005). Invariant visual representation by single neurons in the human brain. Nature. 435 [PubMed]

Rao RP. (1999). An optimal estimation approach to visual perception and learning. Vision research. 39 [PubMed]

Rao RP, Ballard DH. (1997). Dynamic model of visual recognition predicts neural response properties in the visual cortex. Neural computation. 9 [PubMed]

Riesenhuber M, Poggio T. (1999). Hierarchical models of object recognition in cortex. Nature neuroscience. 2 [PubMed]

Rolls ET, Milward T. (2000). A model of invariant object recognition in the visual system: learning rules, activation functions, lateral inhibition, and information-based performance measures. Neural computation. 12 [PubMed]

Sejnowski TJ, Ackley DH, Hinton GE. (1985). A learning algorithm for Bolzmann machines. Cognitive Sci. 9

Sejnowski TJ, Hinton GE. (1983). Optimal perceptual inference. Proc. IEEE Computer Soc. Conf. on Vision and Pattern Recognition..

Sereno MI et al. (1995). Borders of multiple visual areas in humans revealed by functional magnetic resonance imaging. Science (New York, N.Y.). 268 [PubMed]

Sompolinsky H. (1988). Statistical mechanics of neural networks Physics Today. 41

Stevens CF. (2001). An evolutionary scaling law for the primate visual system and its basis in cortical function. Nature. 411 [PubMed]

Thorpe S, Fize D, Marlot C. (1996). Speed of processing in the human visual system. Nature. 381 [PubMed]

Vinje WE, Gallant JL. (2000). Sparse coding and decorrelation in primary visual cortex during natural vision. Science (New York, N.Y.). 287 [PubMed]

Virasoro MA, Mezard M, Parisi G. (1987). Spin glass theory and beyond.

Welling M, Teh YW. (2003). Approximate inference in Boltzmann machines Artificial Intelligence. 143

Williams RJ, Peng J. (1990). An efficient gradient-based algorithm for on-line training of recurrent network trajectories Neural Comput. 2

Willsky AS, Freeman WT, Sudderth EB, Torralba A. (2005). Learning hierarchical models of scenes, objects and parts Intl Conf Comput Vis. 2