5 accepted papers
Examining the dynamic aspects of functional networks in the brain is imperative in order to obtain a thorough description and to gain a better insight into its several features. Present methods of analysing brain data in task-conditions mainly include concatenation followed by temporal correlation.…
In this paper we present a Bayesian method for parameter estimation in linear Jump-Langevin systems, i.e. systems driven by a linear, mean-reverting jump-diffusion trend process. Such models have been applied successfully to trend following in finance, in order to develop momentum-based trading stra…
We propose a novel probabilistic inference approach that permits predicting, well in advance, the intended destination of a pointing gesture aimed at selecting an icon on an in-vehicle interactive display. It models the partial 3D pointing track as a Markov bridge terminating at a nominal destinatio…
This paper presents an O(n <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">4</sup> ) time method for filtering and sampling of a time-varying n × n system matrix A <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/x…
Recent empirical research has discovered that linkages among fMRI signals of the brain in resting-state have meaningful temporal variations. Most current studies of brain networks assume that these linkages are constant. We propose a model and an accompanying algorithm to infer and track changes in…