A statistical generative model is presented as an alternative to negative selection in anomaly detection of string data. We extend the probabilistic approach to binary classificat...
Model-based development has become state of the art in software engineering. A number of tools, like Matlab/Simulink or SCADE, are available for the automatic generation of applic...
Christian Buckl, Matthias Regensburger, Alois Knol...
We introduce a generative model of dense flow fields within a layered representation of 3-dimensional scenes. Using probabilistic inference and learning techniques (namely, varia...
This paper presents a methodology to automate natural language requirements analysis and class model generation based on the Rational Unified Process (RUP). Use-case language schem...
We present a formal model and a simple architecture for robust pseudorandom generation that ensures resilience in the face of an observer with partial knowledge/control of the gen...