Designing modern circuits comprised of millions of gates is a very challenging task. Therefore new directions are investigated for efficient modeling and verification of such syst...
Learning dynamic Bayesian network structures provides a principled mechanism for identifying conditional dependencies in time-series data. An important assumption of traditional D...
Given a multi-exposure sequence of a scene, our aim is to recover the absolute irradiance falling onto a linear camera sensor. The established approach is to perform a weighted av...
Miguel Granados Velasquez, Boris Ajdin, Michael Wa...
We propose a discriminative learning approach for fusing multichannel sequential data with application to detect unsafe driving patterns from multi-channel driving recording data....
Abstract: Event-driven Process Chains (EPCs) are a commonly used modelling technique for design and documentation of business processes. Although EPCs have an easy-to-understand no...