We present applications of a recently developed automated nonlinear macromodelling approach to the important problem of macromodelling high-speed output buffers/drivers. Good nonl...
Abstract. In this paper, we present a methodology for performing statistical analysis for image-based studies of differences between populations and describe our experience applyin...
Polina Golland, Bruce Fischl, Mona Spiridon, Nancy...
This paper presents a novel statistical fuzzy-segmentation method for diffusion tensor (DT) images and magnetic resonance (MR) images. Typical fuzzy-segmentation schemes, e.g. thos...
This paper presents a method for detection of cerebral white matter hyperintensities (WMH) based on run-time PD-, T1-, and T2weighted structural magnetic resonance (MR) images of t...
Charles DeCarli, Christopher Schwarz, Evan Fletche...
In this paper, we introduce a generic framework for semi-supervised kernel learning. Given pairwise (dis-)similarity constraints, we learn a kernel matrix over the data that respe...