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NIPS
2007
13 years 9 months ago
Bayesian Inference for Spiking Neuron Models with a Sparsity Prior
Generalized linear models are the most commonly used tools to describe the stimulus selectivity of sensory neurons. Here we present a Bayesian treatment of such models. Using the ...
Sebastian Gerwinn, Jakob Macke, Matthias Seeger, M...
CEC
2008
IEEE
14 years 1 months ago
Reduced polynomial neural swarm net for classification task in data mining
—In this paper, we proposed a reduced polynomial neural swarm net (RPNSN) for the task of classification. Classification task is one of the most studied tasks of data mining. In ...
Bijan Bihari Misra, Satchidananda Dehuri, Pradipta...
INFORMATICALT
2008
120views more  INFORMATICALT 2008»
13 years 7 months ago
Nonlinear Behaviour in the MPI-Parallelised Model of the Rat Somatosensory Cortex
Mammalian brains consisting of up to 1011 neurons belong to group of the most complex systems in the Universe. For years they have been one of the hardest objects of simulation. Th...
Grzegorz M. Wojcik, Wieslaw A. Kaminski
NIPS
2003
13 years 8 months ago
Predicting Speech Intelligibility from a Population of Neurons
A major issue in evaluating speech enhancement and hearing compensation algorithms is to come up with a suitable metric that predicts intelligibility as judged by a human listener...
Jeff Bondy, Ian C. Bruce, Suzanna Becker, Simon Ha...
BMCBI
2006
101views more  BMCBI 2006»
13 years 7 months ago
Predicting residue contacts using pragmatic correlated mutations method: reducing the false positives
Background: Predicting residues' contacts using primary amino acid sequence alone is an important task that can guide 3D structure modeling and can verify the quality of the ...
Petras J. Kundrotas, Emil Alexov