Large-scale process fluctuations (particularly random device mismatches) at nanoscale technologies bring about highdimensional strongly nonlinear performance variations that canno...
We present learning and inference algorithms for a versatile class of partially observed vector autoregressive (VAR) models for multivariate time-series data. VAR models can captu...
A fundamental problem when computing statistical shape models is the determination of correspondences between the instances of the associated data set. Often, homologies between po...
Heike Hufnagel, Xavier Pennec, Jan Ehrhardt, Heinz...
In context-dependent acoustic modeling, it is important to strike a balance between detailed modeling and data sufficiency for robust estimation of model parameters. In the past,...
— A vocal imitation system was developed using a computational model that supports the motor theory of speech perception. A critical problem in vocal imitation is how to generate...