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CSDA
2007
131views more  CSDA 2007»
13 years 4 months ago
Bivariate density estimation using BV regularisation
In this paper we study the problem of bivariate density estimation. The aim is to find a density function with the smallest number of local extreme values which is adequate with ...
Andreas Obereder, Otmar Scherzer, Arne Kovac
JCNS
2000
165views more  JCNS 2000»
13 years 4 months ago
A Population Density Approach That Facilitates Large-Scale Modeling of Neural Networks: Analysis and an Application to Orientati
We explore a computationally efficient method of simulating realistic networks of neurons introduced by Knight, Manin, and Sirovich (1996) in which integrate-and-fire neurons are ...
Duane Q. Nykamp, Daniel Tranchina
CVPR
2008
IEEE
14 years 6 months ago
Conditional density learning via regression with application to deformable shape segmentation
Many vision problems can be cast as optimizing the conditional probability density function p(C|I) where I is an image and C is a vector of model parameters describing the image. ...
Jingdan Zhang, Shaohua Kevin Zhou, Dorin Comaniciu...
AMC
2008
94views more  AMC 2008»
13 years 4 months ago
Modeling and inversion of net ecological exchange data using an Ito stochastic differential equation approach
A system of stochastic differential equations is studied describing a compartmental carbon transfer model that includes uncertainties arising in the model from environmental and p...
Luther White, Yiqi Luo
BMCBI
2010
175views more  BMCBI 2010»
13 years 4 months ago
Global parameter estimation methods for stochastic biochemical systems
Background: The importance of stochasticity in cellular processes having low number of molecules has resulted in the development of stochastic models such as chemical master equat...
Suresh Kumar Poovathingal, Rudiyanto Gunawan