Importance sampling-based algorithms are a popular alternative when Bayesian network models are too large or too complex for exact algorithms. However, importance sampling is sensi...
We present a Bayesian approach to color constancy which utilizes a nonGaussian probabilistic model of the image formation process. The parameters of this model are estimated direc...
Charles R. Rosenberg, Thomas P. Minka, Alok Ladsar...
: Kernel density estimation for multivariate data is an important technique that has a wide range of applications. However, it has received significantly less attention than its un...
Abstract. This paper presents a formal verification algorithm for finding errors in models of complex concurrent systems. The algorithm improves explicit guided model checking by a...
The problem considered in this paper is that of estimating the projective transformation between two images in situations where the image motion is large and featurematching is no...