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We introduce a novel framework for simultaneous structure and parameter learning in hidden-variable conditional probability models, based on an entropic prior and a solution for i...
We approach the problem of stylistic motion synthesis by learning motion patterns from a highly varied set of motion capture sequences. Each sequence may have a distinct choreogra...
This paper addresses several aspects related to the distribution of content. The first aim is to provide an overview of the Universal Multimedia Access (UMA) concept. The primary...