We present a sparse approximation approach for dependent output Gaussian processes (GP). Employing a latent function framework, we apply the convolution process formalism to estab...
Functional magnetic resonance imaging (fMRI) is a popular tool for studying brain activity due to its non-invasiveness. Conventionally an expected response needs to be available f...
Sarah Lee, Fernando Zelaya, Yohan Samarasinghe, St...
This paper presents an interactive transfer function design tool based on ellipsoidal Gaussian transfer functions (ETFs). Our approach explores volumetric features in the statisti...
In this paper, a new framework for brain warping via landmark matching is proposed using implicit representations or the level set method. We demonstrate this powerful technique b...
Alexia Leow, Paul M. Thompson, Hillary Protas, Sun...
—We consider distributed estimation of the inverse covariance matrix in Gaussian graphical models. These models factorize the multivariate distribution and allow for efficient d...