Many techniques of knowledge-based segmentation consist of building statistical models that describe the deformations of the structure of interest, and then fit these models to t...
Charles Florin, Nikos Paragios, Gareth Funka-Lea, ...
Despite significant research on state-space reductions, the poor scalability of model checking for reasoning about behavioral models of large, complex systems remains the chief ob...
Matthew B. Dwyer, Robby, Xianghua Deng, John Hatcl...
Research has shown promise in the design of large scale common sense probabilistic models to infer human state from environmental sensor data. These models have made use of mined ...
William Pentney, Matthai Philipose, Jeff A. Bilmes
Inspectable Bayesian student models have been used to support student reflection, knowledge awareness and communication among teacher, students and parents. This paper presents a...
Short, high-dimensional, Multivariate Time Series (MTS) data are common in many fields such as medicine, finance and science, and any advance in modelling this kind of data would b...
Paul Kellam, Xiaohui Liu, Nigel J. Martin, Christi...