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» Bayesian inference in spiking neurons
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NIPS
2003
13 years 6 months ago
Information Dynamics and Emergent Computation in Recurrent Circuits of Spiking Neurons
We employ an efficient method using Bayesian and linear classifiers for analyzing the dynamics of information in high-dimensional states of generic cortical microcircuit models....
Thomas Natschläger, Wolfgang Maass
ECML
2007
Springer
13 years 11 months ago
Bayesian Inference for Sparse Generalized Linear Models
We present a framework for efficient, accurate approximate Bayesian inference in generalized linear models (GLMs), based on the expectation propagation (EP) technique. The paramete...
Matthias Seeger, Sebastian Gerwinn, Matthias Bethg...
NIPS
2004
13 years 6 months ago
Probabilistic Computation in Spiking Populations
As animals interact with their environments, they must constantly update estimates about their states. Bayesian models combine prior probabilities, a dynamical model and sensory e...
Richard S. Zemel, Quentin J. M. Huys, Rama Nataraj...
SP
2008
IEEE
159views Security Privacy» more  SP 2008»
13 years 4 months ago
Inferring neuronal network connectivity from spike data: A temporal data mining approach
Abstract. Understanding the functioning of a neural system in terms of its underlying circuitry is an important problem in neuroscience. Recent developments in electrophysiology an...
Debprakash Patnaik, P. S. Sastry, K. P. Unnikrishn...
NECO
2008
106views more  NECO 2008»
13 years 4 months ago
Bayesian Spiking Neurons II: Learning
Sophie Deneve