A scalable macromodel for substrate noise coupling in heavily doped substrates has been developed. This model is simple since it requires only four parameters which can readily be ...
Time-series segmentation in the fully unsupervised scenario in which the number of segment-types is a priori unknown is a fundamental problem in many applications. We propose a Ba...
We introduce Gaussian process dynamical models (GPDMs) for nonlinear time series analysis, with applications to learning models of human pose and motion from high-dimensional motio...
In this work1 we obtain robust category-based language models to be integrated into speech recognition systems. Deductive rules are used to select linguistic categories and to matc...
In this paper we present a volume data model amenable to querying volumes in databases. Unlike most existing volume models, which are directed towards specific applications (notab...