— We present a waveform based variational static timing analysis methodology. It is a timing paradigm that lies midway between convention static delay approximations and full dyn...
Variational methods have proved popular and effective for inference and learning in intractable graphical models. An attractive feature of the approaches based on the Kullback-Lei...
We propose a convex variational framework to compute high resolution images from a low resolution video. The image formation process is analyzed to provide to a well designed model...
Markus Unger, Thomas Pock, Manuel Werlberger, Hors...
Recently, several learning algorithms relying on models with deep architectures have been proposed. Though they have demonstrated impressive performance, to date, they have only b...
Hugo Larochelle, Dumitru Erhan, Aaron C. Courville...
Abstract. UML activity diagrams have become an established notamodel control and data flow on various levels of abstraction, ranging from fine-grained descriptions of algorithms ...