The Gaussian process latent variable model (GP-LVM) is a generative approach to nonlinear low dimensional embedding, that provides a smooth probabilistic mapping from latent to da...
In multi-target tracking, the maintaining of the correct identity of targets is challenging. In the presented tracking method, accurate target identification is achieved by incor...
We propose an unsupervised, probabilistic method for learning visual feature hierarchies. Starting from local, low-level features computed at interest point locations, the method c...
We evaluate probabilistic models of verb argument structure trained on a corpus of verbs and their syntactic arguments. Models designed to represent patterns of verb alternation b...
Abstract. Explanation based learning produces generalized explanations from examples. These explanations are typically built in a deductive manner and they aim to capture the essen...