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Dissertation
Explaining and Visualizing Structural Knowledge in Bipartite Graphs
(2023)
Bipartite graphs are an important model for the representation and analysis of relationships between two different types of entities. Datasets in this form are commonly found in many fields, such as social networks, biology, and economics. Formal concept analysis is a research approach that allows for the analysis of such bipartite graphs by clustering the data into so-called concepts and ordering those in a lattice structure.
In this thesis we propose multiple approaches for the extraction and visualization of ...
Dissertation
Learning planning communication in cooperative multi-agent settings
(2023)
This work is a holistic investigation of the question of how and why reinforcement learning (RL) agents fail to develop planning communication in a cooperative setting. It is also a guide to anyone trying to build a system that learns to use planning communication patterns. We examine the state of the art in multi-agent systems and emergent communication for the existence of communication patterns that share information about future actions and plans. To do this, we strategically formulate hypotheses that question ...
Dissertation
Attribute Exploration with Multiple Experts
(2023)
Attribute exploration is a knowledge acquisition method from the realm of formal concept analysis that allows a domain expert to efficiently uncover the dependencies in a domain. It is based on a question-answering scheme where the exploration algorithm generates questions about dependencies in the domain that are then answered by a domain expert. Even though many variants and extension to this were developed, only few attempts to incorporate multiple experts were made. The overarching goal of this thesis is to extend ...
Habilitation
Computing Ground States for Fermi-Bose Mixtures through Efficient Numerical Methods
(2023-05)
In this work, we will first review the Quantum Mechanics theory to derive the main equations. Next, we will analyze these equations by Functional Analysis methods to find conditions for existence, uniqueness, multiplicity, and other properties as positivity. Next, we will review and develop some numerical methods for solving the nonlinear Schrödinger equation, its time version, generalizations with rotational terms, and systems of NLSE (NLSS). We notice that the main problem to run numerical methods is the memory ...
Dissertation
Situative Teams in Cooperative Autonomous Systems
(2023)
Distributed systems have been established in many areas of IT and will play an even more significant role in the future. Such systems are no longer limited to specific fields of application but interconnect many different domains. They encompass, e. g. Cloud Computing, Internet of Things, service robotics, and autonomous vehicles. The integrated sub-systems communicate in order to exchange information and, if necessary, perform tasks together. Moreover, the number of interconnected sub-systems is constantly growing. ...
Dissertation
Investigation and Elimination of Substructures in Formal Concept Analysis focusing on Boolean Suborders and Subcontexts
(2023)
In the field of Formal Concept Analysis, data is mainly presented in so-called formal contexts, which assign to a set of objects their respective attributes. From those concept lattices can be generated, where the objects are grouped with respect to their common attributes to represent the relationships in the data in a way that enhances the understandability for humans. However, since a concept lattice can be of exponential size compared to its associated formal context, the presented relationships often become hard ...
Dissertation
Trajectory Mapping in Physical and Topical Spaces
(2023)
In this dissertation, two different types of trajectories are investigated. In the engfirst part of this work, we investigate methods for the analysis of physical trajectories. We focus on scenarios, in which signal strengths ofWiFi access points are recorded. In detail, they are recorded through smartphone devices by people moving through a building. By means of theWiFi signal strengths, (physical) trajectories of humans are reconstructed, which reflect the locations visited over time. Accurate localization based ...
Dissertation
Orometry, Intrinsic Dimensionality and Learning: Novel Insights into Network Data
(2023-11)
Today, networks are an integral part of our world. Let it be real-life friendship networks or social connections that are based on social media. In this thesis, we contribute to the understanding of networks by studying networks from three different perspectives. First, we adapt notions and concepts from orometry to metric data and networks to gain novel insights from a local perspective. Specifically, we study measures of local outstandingness and propose concepts to derive small hierarchies from larger networks. ...
Aufsatz
Continuous Feature Networks: A Novel Method to Process Irregularly and Inconsistently Sampled Data With Position-Dependent Features
(2023-12-30)
Continuous Kernels have been a recent development in convolutional neural networks. Such kernels are used to process data sampled at different resolutions as well as irregularly and inconsistently sampled data. Convolutional neural networks have the property of translational invariance (e.g., features are detected regardless of their position in the measurement domain), which is unsuitable if the position of detected features is relevant for the prediction task. However, the capabilities of continuous kernels to ...