Abstract— Almost all learning machines used in computational intelligence are not regular but singular statistical models, because they are nonidentifiable and their Fisher info...
— The applicability of complex networks of spiking neurons as a general purpose machine learning technique remains open. Building on previous work using macroscopic exploration o...
We introduce an algorithm that consistently and accurately processes arbitrary intersections in tetrahedral meshes in real-time. The intersection surfaces are modeled up to the cu...
Daniel Bielser, Pascal Glardon, Matthias Teschner,...
This paper proposes the modeling of technical systems and their behavior by means of Unified Modeling Language (UML) State Machines and the extending UML Profile for Schedulabil...
Scientific workflows have recently emerged as a new paradigm for representing and managing complex distributed scientific computations and data analysis, and have enabled and acce...