2 papers
eess.SY2026
Global Parameter Identification and Uncertainty Quantification of reduced-order ADM1 using Maximum Likelihood Estimation and Bayesian Inference
Simon Hellmann, Leander Lerch, Terrance Wilms +6
Anaerobic digestion (AD) models can be challenging to calibrate against real data due to limited practical identifiability, data scarcity, and model complexity. Weighted least squa…
math.OC2026
A constraint dissolving inexact penalty method for optimization problems with geometric constraints
Xiaoxi Jia, Leander Lerch, Stefan Streif +1
Optimization problems with geometric constraints have a broad range of applications, including machine learning, finance, and control. A powerful algorithmic tool to resolve these…