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» Fast computation with neural oscillators
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NIPS
2004
13 years 11 months ago
Rate- and Phase-coded Autoassociative Memory
Areas of the brain involved in various forms of memory exhibit patterns of neural activity quite unlike those in canonical computational models. We show how to use well-founded Ba...
Máté Lengyel, Peter Dayan
ICANN
2010
Springer
13 years 7 months ago
Dynamics and Function of a CA1 Model of the Hippocampus during Theta and Ripples
The hippocampus is known to be involved in spatial learning in rats. Spatial learning involves the encoding and replay of temporally sequenced spatial information. Temporally seque...
Vassilis Cutsuridis, Michael E. Hasselmo
ANNPR
2006
Springer
14 years 1 months ago
Fast Training of Linear Programming Support Vector Machines Using Decomposition Techniques
Abstract. Decomposition techniques are used to speed up training support vector machines but for linear programming support vector machines (LP-SVMs) direct implementation of decom...
Yusuke Torii, Shigeo Abe
ISMB
1993
13 years 11 months ago
Protein Classification Using Neural Networks
Wehave recently described a method based on Artificial Neural Networksto cluster protein sequences into families. The network was trained with Kohonen’s unsupervised-learning al...
Edgardo A. Ferrán, Pascual Ferrara, Bernard...
JCNS
2010
103views more  JCNS 2010»
13 years 4 months ago
Efficient computation of the maximum a posteriori path and parameter estimation in integrate-and-fire and more general state-spa
A number of important data analysis problems in neuroscience can be solved using state-space models. In this article, we describe fast methods for computing the exact maximum a pos...
Shinsuke Koyama, Liam Paninski