This paper presents a novel approach to data fusion for stochastic processes that model spatial data. It addresses the problem of data fusion in the context of large scale terrain ...
Shrihari Vasudevan, Fabio T. Ramos, Eric Nettleton...
This paper describes a novel application of Statistical Learning Theory (SLT) to control model complexity in flow estimation. SLT provides analytical generalization bounds suitabl...
Zoran Duric, Fayin Li, Harry Wechsler, Vladimir Ch...
Algebraic randomization techniques can be applied to hybrid symbolic-numeric algorithms. Here we consider the problem of interpolating a sparse rational function from noisy values...
We describe our visualization process for a particle-based simulation of the formation of the first stars and their impact on cosmic history. The dataset consists of several hundre...
Paul Arthur Navrátil, Jarrett L. Johnson, Volke...
Non-rigid registration is central to many problems in computer vision and medical image analysis. We propose a registration algorithm which is regularized by prior knowledge in th...