Probabilistic functional integrated networks are powerful tools with which to draw inferences from high-throughput data. However, network analyses are generally not tailored to spe...
We present a process-algebraic language for Probabilistic I/O Automata (PIOA). To ensure that PIOA specifications given in our language satisfy the “input-enabled” property, w...
Eugene W. Stark, Rance Cleaveland, Scott A. Smolka
Generic representatives have been proposed for the effective combination of symmetry reduction and symbolic representation with BDDs in non-probabilistic model checking. This appro...
We describe an application of probabilistic modeling and inference technology to the problem of analyzing sensor data in the setting of an intensive care unit (ICU). In particular...
Norm Aleks, Stuart Russell, Michael G. Madden, Dia...
Based on a recent development in the area of error control coding, we introduce the notion of convolutional factor graphs (CFGs) as a new class of probabilistic graphical models. ...