3 papers
cs.LG2024
Dirac--Bianconi Graph Neural Networks -- Enabling Non-Diffusive Long-Range Graph Predictions
Christian Nauck, Rohan Gorantla, Michael Lindner +3
The geometry of a graph is encoded in dynamical processes on the graph. Many graph neural network (GNN) architectures are inspired by such dynamical systems, typically based on the…
eess.SY2024
Predicting Fault-Ride-Through Probability of Inverter-Dominated Power Grids using Machine Learning
Christian Nauck, Anna Büttner, Sebastian Liemann +2
Due to the increasing share of renewables, the analysis of the dynamical behavior of power grids gains importance. Effective risk assessments necessitate the analysis of large numb…
nlin.AO2024
Instability in Complex Oscillator Networks: Limitations and Potentials of Network Measures and Machine Learning
Christian Nauck, Michael Lindner, Nora Molkenthin +4
A central question of network science is how functional properties of systems emerge from their structure. For networked dynamical systems, structure is typically captured through…