Schema learning is a way to discover probabilistic, constructivist, predictive action models (schemas) from experience. It includes methods for finding and using hidden state to m...
Surface triangle meshes and volume data are two commonly used representations of digital geometry. Converting from triangle meshes to volume data is challenging, since triangle mes...
In this paper, we introduce the concept of metavariability, i.e., variability with respect to basic variability attributes like binding time or constraints. While the main focus o...