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In recent years, we have seen a dramatic increase in the amount of video data recorded and stored around the world. Driven by the availability of low-cost video cameras, the ever-decreasing cost of digital media storage, and the explosion in popularity of ...
In recent years, we have seen a dramatic increase in the amount of video data recorded and stored around the world. Driven by the availability of low-cost video cameras, the ever-decreasing cost of digital media storage, and the explosion in popularity of ...
Computing the partition function and the marginals of a global probability distribution are two important issues in any probabilistic inference problem. In a previous work, we presented sub-tree based upper and lower bounds on the partition function of a g ...
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For the multi-robot coverage problem determin- istic deliberative as well as probabilistic approaches have been proposed. Whereas deterministic approaches usually provide provable completeness and promise good performance under perfect conditions, probabil ...
In silico modeling of Gene Regulatory Networks (GRN) has recently aroused a lot of interest in the biological community for modeling and understanding complex pathways. Boolean Networks (BN) are a common modeling tool for in silico dynamic analysis of such ...
The environment that surrounds us is very complex. Understanding and interpreting it is a very hard task. This paper proposes an approach allowing simple form recognition with a camera by using a probabilistic approach called Bayesian Programming. The main ...
Chord progressions are the building blocks from which tonal music is constructed. Inferring chord progressions is thus an essential step towards modeling long term dependencies in music. In this paper, three different representations for chords are designe ...
Chord progressions are the building blocks from which tonal music is constructed. Inferring chord progressions is thus an essential step towards modeling long term dependencies in music. In this paper, a distributed representation for chords is designed su ...
This thesis proposes to analyse symbolic musical data under a statistical viewpoint, using state-of-the-art machine learning techniques. Our main argument is to show that it is possible to design generative models that are able to predict and to generate m ...
This thesis proposes to analyse symbolic musical data under a statistical viewpoint, using state-of-the-art machine learning techniques. Our main argument is to show that it is possible to design generative models that are able to predict and to generate m ...