This paper presents a new functionality of the Automatic Differentiation (AD) Tool tapenade. tapenade generates adjoint codes which are widely used for optimization or inverse prob...
We present a hierarchical generative model for object recognition that is constructed by weakly-supervised learning. A key component is a novel, adaptive patch feature whose width...
Abstract. In our research we are studying how to combine modelling, metamodelling, and reflection to systematically generate middleware configurations that can be targeted at diffe...
Nelly Bencomo, Gordon S. Blair, Geoff Coulson, Tha...
This poster describes a framework that automatically generates learning support scaffolds to guide task-based learning. The aim is to combine the exploratory learning principles p...
It is our belief that the ultimate automatic system for deriving linear algebra libraries should be able to generate a set of algorithms starting from the mathematical specificati...
Paolo Bientinesi, Sergey Kolos, Robert A. van de G...