7 papers
On a mean-field Pontryagin minimum principle for stochastic optimal control
Manfred Opper, Sebastian Reich
This paper outlines a novel extension of the classical Pontryagin minimum (maximum) principle to stochastic optimal control problems. Contrary to the well-known stochastic Pontryag…
Digital Twins: McKean-Pontryagin Control for Partially Observed Physical Twins
Manfred Opper, Sebastian Reich
Optimal control for fully observed diffusion processes is well established and has led to numerous numerical implementations based on, for example, Bellman's principle, model free…
Affine Invariant Langevin Dynamics for rare-event sampling
Deepyaman Chakraborty, Ruben Harris, Rupert Klein +3
We introduce an affine invariant Langevin dynamics (ALDI) framework for the efficient estimation of rare events in nonlinear dynamical systems. Rare events are formulated as Bayesi…
Early Stopping for Ensemble Kalman-Bucy Inversion
Maia Tienstra, Sebastian Reich
Bayesian linear inverse problems aim to recover an unknown signal from noisy observations, incorporating prior knowledge. This paper analyses a data-dependent method to choose the…
Ensemble Kalman-Bucy filtering for nonlinear model predictive control
Sebastian Reich
We consider the problem of optimal control for partially observed dynamical systems. Despite its prevalence in practical applications, there are still very few algorithms available…
Parameter estimation for partially observed second-order diffusion processes
Jan Albrecht, Sebastian Reich
Estimating parameters of a diffusion process given continuous-time observations of the process via maximum likelihood approaches or, online, via stochastic gradient descent or Kalm…