The transformation of the chemical industry to renewable energy and feedstock supply
requires new paradigms for the design of flexible plants,(bio‐) catalysts, and functional …

Tree ensembles can be well-suited for black-box optimization tasks such as algorithm tuning
and neural architecture search, as they achieve good predictive performance with little or no …

Bayesian inference is a key method for estimating parametric uncertainty from data.
However, most Bayesian inference methods require the explicit likelihood function or many …

In many real-world mixed-integer optimization problems from engineering, the side
constraints can be subdivided into two categories: constraints which describe a certain logic …

The design of regression models that are not affected by outliers is an important task which
has been subject of numerous papers within the statistics community for the last decades …

Surrogate models are an efficient method to expedite the process design by superstructure
optimization. For their application in biorefineries' process design, several surrogate models …

Global optimization of processes through machine learning Page 1 Global Optimization of
Processes through Machine Learning Globale Prozessoptimierung durch maschinelles Lernen …