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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...
CORR
2004
Springer
133views Education» more  CORR 2004»
13 years 7 months ago
Information theory, multivariate dependence, and genetic network inference
We define the concept of dependence among multiple variables using maximum entropy techniques and introduce a graphical notation to denote the dependencies. Direct inference of in...
Ilya Nemenman
MICCAI
2008
Springer
14 years 9 months ago
A Local Mutual Information Guided Denoising Technique and Its Application to Self-calibrated Partially Parallel Imaging
Abstract. The application of Partially Parallel Imaging (PPI) techniques to regular clinical Magnetic Resonance Imaging (MRI) studies has brought about the benefit of significantly...
Weihong Guo, Feng Huang
SCVMA
2004
Springer
14 years 1 months ago
Comparison of Edge-Driven Algorithms for Model-Based Motion Estimation
3D-model-based tracking offers one possibility to explicate the manner in which spatial coherence can be exploited for the analysis of image sequences. Two seemingly different ap...
Hendrik Dahlkamp, Artur Ottlik, Hans-Hellmut Nagel
CSDA
2004
124views more  CSDA 2004»
13 years 7 months ago
Fast and robust discriminant analysis
The goal of discriminant analysis is to obtain rules that describe the separation between groups of observations. Moreover it allows to classify new observations into one of the k...
Mia Hubert, Katrien van Driessen