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» Neural networks for computational neuroscience
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NECO
2007
129views more  NECO 2007»
15 years 5 months ago
Variational Bayes Solution of Linear Neural Networks and Its Generalization Performance
It is well-known that, in unidentifiable models, the Bayes estimation provides much better generalization performance than the maximum likelihood (ML) estimation. However, its ac...
Shinichi Nakajima, Sumio Watanabe
ECCC
2000
158views more  ECCC 2000»
15 years 6 months ago
On the Computational Power of Winner-Take-All
This article initiates a rigorous theoretical analysis of the computational power of circuits that employ modules for computing winner-take-all. Computational models that involve ...
Wolfgang Maass
NC
2010
179views Neural Networks» more  NC 2010»
15 years 4 months ago
Representation before computation
My main objective is to point out a fundamental weakness in the conventional conception of computation and suggest a promising way out. This weakness is directly related to a gross...
Lev Goldfarb
ICANN
2009
Springer
15 years 11 months ago
Computing with Probabilistic Cellular Automata
Abstract. We investigate the computational capabilities of probabilistic cellular automata by means of the density classification problem. We find that a specific probabilistic ...
Martin Schüle, Thomas Ott, Ruedi Stoop
NN
2006
Springer
121views Neural Networks» more  NN 2006»
15 years 6 months ago
Mirror neurons and imitation: A computationally guided review
Neurophysiology reveals the properties of individual mirror neurons in the macaque while brain imaging reveals the presence of `mirror systems' (not individual neurons) in th...
Erhan Oztop, Mitsuo Kawato, Michael A. Arbib