UnRAVeL Fall Workshop
Thursday, 16. & Friday, 17. November 2023
The UnRAVeL fall workshop is themed "Recognizing our own potential". We visit our members' chairs and invite former UnRAVeLs to share their experiences.
|Start in Room 9222, Introduction and UnRAVeL Committees
|Intro talks by PhDs 1
|Intro talks by PhDs 2
|Intro talks by PIs
Tamme Emunds: To build or not to build: Estimating the effect of overpass structures for railway junctions
Many infrastructure managers have the goal to increase the capacity of their railway infrastructure due to an increasing demand. While methods for performance calculations of railway line infrastructure are already well established, the determination of railway junction capacity remains a challenge. This work utilizes the concept of queueing theory to develop a method for the capacity calculation of railway junctions, solely depending on their infrastructure layout along with arrival and service rates. The implementation of the introduced approach is based on advanced model-checking techniques. It can be used to decide which infrastructure layout to build, i.e. whether an overpass for the analyzed railway junction is needed. The developed method hence addresses the need for fast and reliable timetable-independent junction evaluation in the long-term railway capacity calculation landscape.
Tobias Winkler: Programmatic Strategy Synthesis: Resolving Nondeterminism in Probabilistic Programs
Markov decision processes (MDPs) are a standard model for sequential decision making and planning in probabilistic environments. MDPs are applied in fields such as robotics, economics, game theory, reinforcement learning, and others. The basic MDP problem is to find a decision rule, also called strategy or policy, that performs well according to some criteria. Numerous methods for constructing good or even optimal strategies for a given MDP exist. In this talk, we are concerned with finding strategies for infinite families of structurally similar MDPs. For example, in a gambling game we may not know our initial budget upfront, and we would like to have a parameterized strategy for all possible budgets. We encode such parameterized MDPs as simple imperative programs enhanced with coin flips and nondeterminstic branching — the latter is used to model the decisions. Our approach, which draws on principles from deductive program verification, most prominently pre- and postconditions as well as loop invariants, resolves these decisions with provable performance guarantees.
Event: Eisenbahnlehr- und Versuchsanlage (@ VIA)
|End of first day
|opt: Get together: Kegeln im Zuhause
|Event: DSME, Meeting Point: Foyer des TZA, Dennewartstr 25-27
|Start in Digital Church, Jülicher Str. 72a, 52070 Aachen
Vincent Grande: Topological Point Cloud Clustering: Taking spectral clustering to the next dimension
We present Topological Point Cloud Clustering (TPCC), a new method to cluster points in an arbitrary point cloud based on their contribution to global topological features. TPCC synthesizes desirable features from spectral clustering and topological data analysis and is based on considering the spectral properties of a simplicial complex associated to the considered point cloud. As it is based on considering sparse eigenvector computations, TPCC is similarly easy to interpret and implement as spectral clustering. However, by focusing not just on a single matrix associated to a graph created from the point cloud data, but on a whole set of Hodge-Laplacians associated to an appropriately constructed simplicial complex, we can leverage a far richer set of topological features to characterize the data points within the point cloud and benefit from the relative robustness of topological techniques against noise.
|Additionally selected talks of our UnRAVeL Alumni.
Open discussion with former UnRAVeL Members: Dr. Marcel Hark, Prof. Dr. Benjamin Kaminski, Dr. Martin Ritzert, Stephan Zieger, Dr. Rebecca Haehn, Dr. Björn Tauer
|Split feedback on UnRAVeL
|Feedback on Workshop
|End of Workshop