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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-an2021
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…
physics.data-an2021★ 11 cited
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…