Publications (27)
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…
Physics-based material parameters extraction from perovskite experiments via Bayesian optimization
Hualin Zhan, Viqar Ahmad, Azul Mayon +8
The ability to extract material parameters of perovskite from quantitative experimental analysis is essential for rational design of photovoltaic and optoelectronic applications. H…
Linear convergence of accelerated conditional gradient algorithms in spaces of measures
Konstantin Pieper, Daniel Walter
A class of generalized conditional gradient algorithms for the solution of optimization problem in spaces of Radon measures is presented. The method iteratively inserts additional…
Lazifying point insertion algorithms in spaces of measures
Arsen Hnatiuk, Daniel Walter
Greedy point insertion algorithms have emerged as an attractive tool for the solution of minimization problems over the space of Radon measures. Conceptually, these methods can be…
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…
Semiglobal optimal feedback stabilization of autonomous systems via deep neural network approximation
Karl Kunisch, Daniel Walter
A learning approach for optimal feedback gains for nonlinear continuous time control systems is proposed and analysed. The goal is to establish a rigorous framework for computing a…