11 search results - page 1 / 3 » Bayesian Inference for Spiking Neuron Models with a Sparsity... |
NIPS
2007
13 years 6 months ago
2007
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 ...
ECML
2007
Springer
13 years 11 months ago
2007
Springer
We present a framework for efficient, accurate approximate Bayesian inference in generalized linear models (GLMs), based on the expectation propagation (EP) technique. The paramete...
NIPS
2004
13 years 6 months ago
2004
We propose a new interpretation of spiking neurons as Bayesian integrators accumulating evidence over time about events in the external world or the body, and communicating to oth...
NIPS
2004
13 years 6 months ago
2004
There is growing evidence from psychophysical and neurophysiological studies that the brain utilizes Bayesian principles for inference and decision making. An important open quest...
NIPS
2004
13 years 6 months ago
2004
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...