We define a model of learning probabilistic acyclic circuits using value injection queries, in which an arbitrary subset of wires is set to fixed values, and the value on the sing...
Dana Angluin, James Aspnes, Jiang Chen, David Eise...
The following questions are often encountered in system and control theory. Given an algebraic model of a physical process, which variables can be, in theory, deduced from the inp...
The synthesis of stochastic processes using genetic programming is investigated. Stochastic process behaviours take the form of time series data, in which quantities of interest v...
Probabilistic verification of continuous-time stochastic processes has received increasing attention in the model-checking community in the past five years, with a clear focus on ...
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...