Graph-theoretic abstractions are extensively used to analyze massive data sets. Temporal data streams from socioeconomic interactions, social networking web sites, communication t...
Modelling the geometry of organic forms using traditional CAD or animation tools is often difficult and tedious. Different models of morphogenesis have been successfully applied t...
Many complex, real world phenomena are difficult to study directly using controlled experiments. Instead, the use of computer simulations has become commonplace as a feasible alte...
The goal of process mining is to discover process models from event logs. However, for processes that are not well structured and have a lot of diverse behavior, existing process m...
We propose Merge Growing Neural Gas (MGNG) as a novel unsupervised growing neural network for time series analysis. MGNG combines the state-of-the-art recursive temporal context of...
Andreas Andreakis, Nicolai von Hoyningen-Huene, Mi...