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We consider approximate inference in a class of switching linear Gaussian State Space models which includes the switching Kalman Filter and the more general case of switch transitions dependent on the continuous hidden state. The method is a novel form of ...
Automatic meeting analysis is an emerging research field. In this paper, we present stochastic algorithms for tracking people in multi-sensor meeting rooms, for a number of relevant tasks, including tracking multiple people, tracking head pose towards anal ...
In the current work we present two generalizations of the Parallel Tempering algorithm, inspired by the so-called continuous-time Infinite Swapping algorithm. Such a method, found its origins in the molecular dynamics community, and can be understood as th ...
A Monte-Carlo method is used to calibrate a randomly placed sensor node using helicopter sounds. The calibration is based on using the GPS information from the helicopter and the estimated DOA's at the node. The related Cramer-Rao lower bound is derived an ...
We consider approximate inference in a class of switching linear Gaussian State Space models which includes the switching Kalman Filter and the more general case of switch transitions dependent on the continuous hidden state. The method is a novel form of ...
The present work is related to the recent research topics in hydrology devoted to the integration of field knowledge into the hydrological modelling. The study catchment is the Haute-Mentue experimental basin (12.5 km2) located in western Switzerland, in t ...
Automatic meeting analysis is an emerging research field. In this paper, we present stochastic algorithms for tracking people in multi-sensor meeting rooms, for a number of relevant tasks, including tracking multiple people, tracking head pose towards anal ...
