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The problem of control synthesis to maximize the probability of satisfying automata specifications for systems with uncertainty is addressed. Two types of uncertainty are considered; stochasticity in the dynamical system and in the sets defining the specif ...
A new adaptive path interpolation method has been recently developed as a simple and versatile scheme to calculate exactly the asymptotic mutual information of Bayesian inference problems defined on dense factor graphs. These include random linear and gene ...
In this thesis, we study systems of linear and/or non-linear stochastic heat equations and fractional heat equations in spatial dimension 1 driven by space-time white noise. The main topic is the study of hitting probabilities for the solutions to these ...
The present invention concerns a method for a communication device to transmit a data packet in a wireless communication system. The method comprises: determining (21) a first set of transmission parameters comprising a first central transmission frequency ...
In developing countries, the waterborne transmission of hepatitis E virus (HEV), particularly the genotypes 1 and 2, leads to the onset of large recurrent outbreaks. In order to identify the geographical regions at higher risk of HEV epidemics and the cond ...
In this work, we address the problem of query by example spoken term detection (QbE-STD) in zero-resource scenario. State of the art solutions usually rely on dynamic time warping (DTW) based template matching. In contrast, we propose here to tackle the pr ...
High-value infrastructure elements, such as bridges, are typically over-designed. Model-updating techniques are useful for estimating the reserve load capacity (beyond safety factors) of bridges and this improves sustainability through good asset-managemen ...
Mean Field inference is central to statistical physics. It has attracted much interest in the Computer Vision community to efficiently solve problems expressible in terms of large Conditional Random Fields. However, since it models the posterior probabilit ...
Intelligent tutoring systems adapt the curriculum to the needs of the individual student. Therefore, an accurate representation and prediction of student knowledge is essential. Bayesian Knowledge Tracing (BKT) is a popular approach for student modeling. T ...
Mean Field inference is central to statistical physics. It has attracted much interest in the Computer Vision community to efficiently solve problems expressible in terms of large Conditional Random Fields. However, since it models the posterior probabilit ...