8 papers
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…
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…
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…
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…
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…
Filtered data based estimators for stochastic processes driven by colored noise
Grigorios A. Pavliotis, Sebastian Reich, Andrea Zanoni
We consider the problem of estimating unknown parameters in stochastic differential equations driven by colored noise, which we model as a sequence of Gaussian stationary processes…
Particle-based algorithm for stochastic optimal control
Sebastian Reich
The solution to a stochastic optimal control problem can be determined by computing the value function from a discretization of the associated Hamilton-Jacobi-Bellman equation. Alt…