2 citations · 2 across the 5 of their papers we have counts for
9 papers · 1 filter
Stochastic optimal control for nonlinear damped network dynamics
Simone Göttlich, Thomas Schillinger
We present a stochastic optimal control problem for a tree network. The dynamics of the network are governed by transport equations with a special emphasis on the non-linear dampin…
Parameter calibration with Consensus-based Optimization for interaction dynamics driven by neural networks
Simone Göttlich, Claudia Totzeck
We calibrate parameters of neural networks that model forces in interaction dynamics with the help of the Consensus-based global optimization method (CBO). We state the general fra…
Space mapping-based optimization with the macroscopic limit of interacting particle systems
Jennifer Weißen, Simone Göttlich, Claudia Totzeck
We propose a space mapping-based optimization algorithm for microscopic interacting particle dynamics which are inappropriate for direct optimization. This is of relevance for exam…
Optimal control for interacting particle systems driven by neural networks
Simone Göttlich, Claudia Totzeck
We propose a neural network approach to model general interaction dynamics and an adjoint based stochastic gradient descent algorithm to calibrate its parameters. The parameter cal…
Input-to-state stability of a scalar conservation law with nonlocal velocity
Simone Göttlich, Michael Herty, Gediyon Weldegiyorgis
In this paper, we study input-to-state stability (ISS) of an equilibrium for a scalar conservation law with nonlocal velocity and measurement error arising in a highly re-entrant m…
Uncertainty quantification with risk measures in production planning
Simone Göttlich, Stephan Knapp
This paper is concerned with a simulation study for a stochastic production network model, where the capacities of machines may change randomly. We introduce performance measures m…