Probabilistic models of languages are fundamental to understand and learn the profile of the subjacent code in order to estimate its entropy, enabling the verification and predicti...
Abstract. We propose a novel probabilistic framework to merge information from DWI tractography and resting-state fMRI correlations. In particular, we model the interaction of late...
Archana Venkataraman, Yogesh Rathi, Marek Kubicki,...
We describe a class of translation model in which a set of input variants encoded as a context-free forest is translated using a finitestate translation model. The forest structur...
Discrete-Time Markov Chains (DTMCs) are a widely-used formalism to model probabilistic systems. On the one hand, available tools like PRISM or MRMC offer efficient model checking a...
A novel method for quantitatively measuring social interactions on small temporal and spatial scales on the basis of interaction geometry (reduced to the parameters interpersonal d...
Georg Groh, Alexander Lehmann, Jonas Reimers, Marc...