Abstract. The Bayesian approach to machine learning amounts to inferring posterior distributions of random variables from a probabilistic model of how the variables are related (th...
Abstract. Model-Driven Engineering places models as first-class artifacts throughout the software lifecycle requiring the availability of proper transformation languages. Although...
As social networks are becoming ubiquitous on the Web, the Semantic Web goals indicate that it is critical to have a standard model allowing exchange, interoperability, transformat...
In the framework of graph transformation, simulation rules define the operational behavior of visual models. Moreover, it has been shown already how to construct animation rules f...
In this paper, we present new solutions for the interactive modeling of city layouts that combine the power of procedural modeling with the flexibility of manual modeling. Proced...
Markus Lipp, Daniel Scherzer, Peter Wonka, Michael...