Abstract: 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. Ideally, ...

Abstract: Bayesian Network is a significant graphical model that is used to do probabilistic inference and reasoning under uncertainty circumstances. In many applications, existence of discrete and ...

What Is A Probability Density Function? A probability density function, also known as a bell curve, is a fundamental statistics concept, that describes the likelihood of a continuous random variable ...

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Advances in Applied Probability, Vol. 19, No. 3 (Sep., 1987), pp. 632-651 (20 pages) We consider a class of functions on [0,∞), denoted by Ω , having Laplace transforms with only negative zeros and ...