We propose a fully Bayesian approach for generalized kernel models (GKMs), which are extensions of generalized linear models in the feature space induced by a reproducing kernel. ...
Zhihua Zhang, Guang Dai, Donghui Wang, Michael I. ...
:We formulate structure from motion as a Bayesian inference problem, and use a Markov chain Monte Carlo sampler to sample the posterior on this problem. This results in a method th...
This article presents a novel integrated approach to object of interest extraction, including learning to define target pattern and extracting by combining detection and segmenta...
To improve the predictions in dynamic data driven simulations (DDDAS) for subsurface problems, we propose the permeability update based on observed measurements. Based on measurem...
Craig C. Douglas, Yalchin Efendiev, Richard E. Ewi...
Mutual information has become a popular similarity measure in multi-modality medical image registration since it was first applied to the problem in 1995. This paper describes a m...