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» Inference for Multiplicative Models
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104
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NIPS
2007
15 years 2 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...
110
Voted
IJAR
2010
91views more  IJAR 2010»
14 years 11 months ago
Inference and risk measurement with the pari-mutuel model
We explore generalizations of the pari-mutuel model (PMM), a formalization of an intuitive way of assessing an upper probability from a precise one. We discuss a naive extension o...
Renato Pelessoni, Paolo Vicig, Marco Zaffalon
101
Voted
ICIP
2008
IEEE
16 years 2 months ago
Photon-limited image denoising by inference on multiscale models
We present an improved statistical model of Poisson processes, with applications in photon-limited imaging. We build on previous work, adopting a multiscale representation of the ...
Stamatios Lefkimmiatis, George Papandreou, Petros ...
106
Voted
EDM
2010
160views Data Mining» more  EDM 2010»
15 years 2 months ago
Using Neural Imaging and Cognitive Modeling to Infer Mental States while Using an Intelligent Tutoring System
Functional magnetic resonance imaging (fMRI) data were collected while students worked with a tutoring system that taught an algebra isomorph. A cognitive model predicted the distr...
Jon M. Fincham, John R. Anderson, Shawn Betts, Jen...
NIPS
1998
15 years 2 months ago
Fisher Scoring and a Mixture of Modes Approach for Approximate Inference and Learning in Nonlinear State Space Models
We present Monte-Carlo generalized EM equations for learning in nonlinear state space models. The dif
Thomas Briegel, Volker Tresp