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Maximilian Katzmann

Informatiker

Name	Maximilian Katzmann
Ort	Potsdam (Wirkungsort) Deutschland
Akademischer Grad bzw. Titel	Dr.
Beruf	Informatiker (charakteristischer Beruf)
Beziehung	Universität Potsdam Hasso-Plattner-Institut für Digital Engineering
Weitere Angaben	Promotion Potsdam, Universität, Digital Engineering Fakultät, 2023
Datensatztyp	Person
GND-Nummer	1283665166
Datensatz-ID	1283665166
Beteiligt an alle anzeigen Efficiently Approximating Vertex Cover on Scale-Free Networks with Underlying Hyperbolic Geometry About the analysis of algorithms on networks with underlying hyperbolic geometry On the Giant Component of Geometric Inhomogeneous Random Graphs Partitioning the Bags of a Tree Decomposition into Cliques Strongly Hyperbolic Unit Disk Graphs Solving Vertex Cover in Polynomial Time on Hyperbolic Random Graphs Efficiently Approximating Vertex Cover on Scale-Free Networks with Underlying Hyperbolic Geometry Force-Directed Embedding of Scale-Free Networks in the Hyperbolic Plane Solving Vertex Cover in Polynomial Time on Hyperbolic Random Graphs Efficiently Generating Geometric Inhomogeneous and Hyperbolic Random Graphs Efficient Shortest Paths in Scale-Free Networks with Underlying Hyperbolic Geometry

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Katalog der Deutschen Nationalbibliothek

Maximilian Katzmann

Efficiently Approximating Vertex Cover on Scale-Free Networks with Underlying Hyperbolic Geometry

About the analysis of algorithms on networks with underlying hyperbolic geometry

On the Giant Component of Geometric Inhomogeneous Random Graphs

Partitioning the Bags of a Tree Decomposition into Cliques

Strongly Hyperbolic Unit Disk Graphs

Solving Vertex Cover in Polynomial Time on Hyperbolic Random Graphs

Efficiently Approximating Vertex Cover on Scale-Free Networks with Underlying Hyperbolic Geometry

Force-Directed Embedding of Scale-Free Networks in the Hyperbolic Plane

Solving Vertex Cover in Polynomial Time on Hyperbolic Random Graphs

Efficiently Generating Geometric Inhomogeneous and Hyperbolic Random Graphs

Efficient Shortest Paths in Scale-Free Networks with Underlying Hyperbolic Geometry