106 citations · 361 across the 21 of their papers we have counts for
7 papers · 1 filter
Non-linear, bivariate stochastic modelling of power-grid frequency applied to islands
Ulrich Oberhofer, Leonardo Rydin Gorjão, G. Cigdem Yalcin +3
Mitigating climate change requires a transition away from fossil fuels towards renewable energy. As a result, power generation becomes more volatile and options for microgrids and…
Efficient Bayesian estimation of a non-Markovian Langevin model driven by correlated noise
Clemens Willers, Oliver Kamps
Data-driven modeling of non-Markovian dynamics is a recent topic of research with applications in many fields such as climate research, molecular dynamics, biophysics, or wind powe…
Quantifying resilience and the risk of regime shifts under strong correlated noise
Martin Heßler, Oliver Kamps
Early warning indicators often suffer from the shortness and coarse-graining of real-world time series. Furthermore, the typically strong and correlated noise contributions in real…
Bayesian on-line anticipation of critical transitions
Martin Heßler, Oliver Kamps
The design of reliable indicators to anticipate critical transitions in complex systems is an im portant task in order to detect a coming sudden regime shift and to take action in…
Efficient Bayesian estimation of the generalized Langevin equation from data
Clemens Willers, Oliver Kamps
Modeling non-Markovian time series is a recent topic of research in many fields such as climate modeling, biophysics, molecular dynamics, or finance. The generalized Langevin equat…
Non-parametric estimation of a Langevin model driven by correlated noise
Clemens Willers, Oliver Kamps
Langevin models are frequently used to model various stochastic processes in different fields of natural and social sciences. They are adapted to measured data by estimation techni…