106 citations · 361 across the 21 of their papers we have counts for
Showing 2022 · physics.data-anShow all
2 papers · 2 filters
physics.data-an2022
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…
physics.data-an2022★ 10 cited
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…