Continual learning models allow them to learn and adapt to new changes and tasks over time. However, in continual and sequential learning scenarios, in which the models are trained using different ...

There's nothing to get a scientist's heart pumping like a good, old-fashioned statistical debate. When it comes to topics ...

Deep Neural Networks (DNNs) have gained tremendous popularity in many application areas over the recent years. Safety-critical applications as found in the aerospace domain require that the behavior ...

Objectives To compare two Bayesian models capable of identifying unusual and unstable temporal patterns in spatiotemporal data. Setting Annual counts of mammography screening users from each ...

The maze of oil rigs, pipelines, cables and other offshore installations are vulnerable to submarine landslides. The ability ...