activity
20182023
most citedExoplanet Characterization using Conditional Invertible Neural Networks

30 citations · 94 across the 15 of their papers we have counts for

collaborators

15 papers

math.OC2023

Stabilizability for nonautonomous linear parabolic equations with actuators as distributions

Karl Kunisch, Sérgio S. Rodrigues, Daniel Walter

The stabilizability of a general class of abstract parabolic-like equations is investigated, with a finite number of actuators. This class includes the case of actuators given as d…

math.NA2023★ 3 cited

Towards optimal sensor placement for inverse problems in spaces of measures

Phuoc-Truong Huynh, Konstantin Pieper, Daniel Walter

The objective of this work is to quantify the reconstruction error in sparse inverse problems with measures and stochastic noise, motivated by optimal sensor placement. To be usefu…

math.OC2022★ 6 cited

Extremal points and sparse optimization for generalized Kantorovich-Rubinstein norms

Marcello Carioni, José A. Iglesias, Daniel Walter

A precise characterization of the extremal points of sublevel sets of nonsmooth penalties provides both detailed information about minimizers, and optimality conditions in general…

math.OC2022★ 1 cited

Learning Optimal Feedback Operators and their Polynomial Approximation

Karl Kunisch, Donato Vásquez-Varas, Daniel Walter

A learning based method for obtaining feedback laws for nonlinear optimal control problems is proposed. The learning problem is posed such that the open loop value function is its…

astro-ph.EP2022★ 30 cited

Exoplanet Characterization using Conditional Invertible Neural Networks

Jonas Haldemann, Victor Ksoll, Daniel Walter +6

The characterization of an exoplanet's interior is an inverse problem, which requires statistical methods such as Bayesian inference in order to be solved. Current methods employ M…

math.OC2021★ 1 cited

Extremal points of total generalized variation balls in 1D: characterization and applications

José A. Iglesias, Daniel Walter

The total generalized variation (TGV) is a popular regularizer in inverse problems and imaging combining discontinuous solutions and higher order smoothing. In particular, empirica…