unsupervised construction of topological maps, which provide an abstraction of the environment in terms of visual aspects. An unsupervised clustering algorithm is used to represent...
There is an obvious need for improving the performance and accuracy of a Bayesian network as new data is observed. Because of errors in model construction and changes in the dynam...
Abstract— The optimal model parameters of a kernel machine are typically given by the solution of a convex optimisation problem with a single global optimum. Obtaining the best p...
Background: Mocapy++ is a toolkit for parameter learning and inference in dynamic Bayesian networks (DBNs). It supports a wide range of DBN architectures and probability distribut...
Models are increasingly being relied upon to inform and support natural resource management. They are incorporating an ever broader range of disciplines and now often confront peo...
Anthony J. Jakeman, Rebecca A. Letcher, John P. No...