Massive transaction data sets are recorded in a routine manner in telecommunications, retail commerce, and Web site management. In this paper we address the problem of inferring p...
Recent research in machine learning has focused on breaking audio spectrograms into separate sources of sound using latent variable decompositions. These methods require that the ...
A Bayesian approach to analyze the modes of variation in a set of curves is suggested. It is based on a generative model thus allowing for noisy and sparse observations of curves....
We introduce a variational inference framework for training the Gaussian process latent variable model and thus performing Bayesian nonlinear dimensionality reduction. This method...
Abstract. This paper investigates the efficiency of in-door next location prediction by comparing several prediction methods. The scenario concerns people in an office building vis...
Jan Petzold, Andreas Pietzowski, Faruk Bagci, Wolf...