We develop and analyze a numerical two-scale optimization scheme for structural shape optimization. Whenever cost functionals, such as the elastic energy, are subject to minimization, while meeting a constraint on the ...

In the first part of this work we study the gluing of metric measure spaces. The gluing is defined by a bilipschitz map which identifies the gluing sets. The new metric is given by the minimal length of all possible paths ...

Ausgangsfrage dieser Doktorarbeit war die Gleichverteilung von geschlossenen Geodaetischen im Fundamentalbereich der Modulgruppe in der hyperbolischen Geometrie. Das fuehrt auf das Studium der Eigenfunktionen des ...

This thesis is concerned with convergence to stationarity of non-reversible Markov processes with degenerate noise, known as hypocoercivity. We develop a framework that allows to derive rates of convergence towards the ......

Tissue dynamics are complex and involve interactions between different cell types and extracellular components on different spatial and temporal scales. Specific tissue properties are relevant for a broad range of processes, ...

Reinforcement learning is a machine learning paradigm that aims to develop optimal policies for discrete-time control problems based on quantitative feedback on the learner’s behaviour. Reinforcement learning is formulated ...

This thesis studies global routing in chip design, and its generalization, the Load Balancing Problem: finding a minimum-norm element of a structured set built from many "customer" subproblems, each accessible only through ...