Model transformations are playing a vital role in the field of model engineering. However, for non-trivial transformation issues most approaches require imperative definitions, w...
We present a learning algorithm for non-parametric hidden Markov models with continuous state and observation spaces. All necessary probability densities are approximated using sa...
We present a novel approach to speech-driven facial animation using a non-parametric switching state space model based on Gaussian processes. The model is an extension of the shar...
This paper presents a probabilistic relational modelling (implementation) of the major probabilistic retrieval models. Such a high-level implementation is useful since it supports ...
Hidden Markov models (HMMs) have received considerable attention in various communities (e.g, speech recognition, neurology and bioinformatic) since many applications that use HMM...