Increasing the Diversity of Benchmark Function Sets Through Affine Recombination. - Konstantin Dietrich; Olaf Mersmann (PPSN (1), 2022)

Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape Features. - Raphael Patrick Prager; Konstantin Dietrich; Lennart Schneider; Lennart Schäpermeier; Bernd Bischl; Pascal Kerschke; Heike Trautmann; Olaf Mersmann (FOGA, 2023)

Evaluation of Algorithms from the Nevergrad Toolbox on the Strictly Box-Constrained SBOX-COST Benchmarking Suite. - Konstantin Dietrich; Pascal Kerschke (GECCO Companion, 2023)

Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization. - Konstantin Dietrich; Diederick Vermetten; Carola Doerr; Pascal Kerschke (GECCO, 2024)

Hybridizing Target- and SHAP-Encoded Features for Algorithm Selection in Mixed-Variable Black-Box Optimization. - Konstantin Dietrich; Raphael Patrick Prager; Carola Doerr; Heike Trautmann (PPSN (2), 2024)

Impact of Training Instance Selection on Automated Algorithm Selection Models for Numerical Black-box Optimization - Reproducibility Files. - Konstantin Dietrich; Diederick Vermetten; Carola Doerr; Pascal Kerschke (Zenodo, 2024)