4.5 Article

Predictive coding and the slowness principle: An information-theoretic approach

Related references

Note: Only part of the references are listed.
Article Biochemical Research Methods

Slowness and sparseness lead to place, head-direction, and spatial-view cells

Mathias Franzius et al.

PLOS COMPUTATIONAL BIOLOGY (2007)

Article Computer Science, Artificial Intelligence

Soft mixer assignment in a hierarchical generative model of natural scene statistics

Odelia Schwartz et al.

NEURAL COMPUTATION (2006)

Article Computer Science, Artificial Intelligence

What is the relation between slow feature analysis and independent component analysis?

Tobias Blaschke et al.

NEURAL COMPUTATION (2006)

Article Computer Science, Artificial Intelligence

Multivariate information bottleneck

Noam Slonim et al.

NEURAL COMPUTATION (2006)

Article Biochemistry & Molecular Biology

A model of the ventral visual system based on temporal stability and local memory

Reto Wyss et al.

PLOS BIOLOGY (2006)

Article Multidisciplinary Sciences

Dynamic predictive coding by the retina

T Hosoya et al.

NATURE (2005)

Article Computer Science, Cybernetics

Learning viewpoint invariant object representations using a temporal coherence principle

W Einhäuser et al.

BIOLOGICAL CYBERNETICS (2005)

Article Multidisciplinary Sciences

Invariant visual representation by single neurons in the human brain

RQ Quiroga et al.

NATURE (2005)

Article Computer Science, Artificial Intelligence

A hierarchical Bayesian model for learning nonlinear statistical regularities in nonstationary natural signals

KL Yan et al.

NEURAL COMPUTATION (2005)

Article Ophthalmology

Slow feature analysis yields a rich repertoire of complex cell properties

P Berkes et al.

JOURNAL OF VISION (2005)

Article Computer Science, Artificial Intelligence

Simple-cell-like receptive fields maximize temporal coherence in natural video

J Hurri et al.

NEURAL COMPUTATION (2003)

Article Computer Science, Artificial Intelligence

Slow feature analysis: Unsupervised learning of invariances

L Wiskott et al.

NEURAL COMPUTATION (2002)

Review Computer Science, Artificial Intelligence

Predictability, complexity, and learning

W Bialek et al.

NEURAL COMPUTATION (2001)

Article Computer Science, Artificial Intelligence

Neural coding and decoding: communication channels and quantization

AG Dimitrov et al.

NETWORK-COMPUTATION IN NEURAL SYSTEMS (2001)