This paper introduces a new generalisation of the familiar scale-space and wavelet representations, designed specifically to deal with the complexities of representing motions ind...
Andrew Calway, Peter Meulemans, Roland G. Wilson, ...
Unsupervised word representations are very useful in NLP tasks both as inputs to learning algorithms and as extra word features in NLP systems. However, most of these models are b...
Eric H. Huang, Richard Socher, Christopher D. Mann...
Possibilistic networks and possibilistic logic bases are important tools to deal with uncertain pieces of information. Both of them offer a compact representation of possibility ...
We discuss the role of spatial representations and visual geometries in vision-based navigation. To a large extent, these choices determine the complexity and robustness of a given...
We introduce a new image representation that encompasses both the general layout of groups of quantized local invariant descriptors as well as their relative frequency. A graph of...