| 2024 | PPSN | Hybridizing Target- and SHAP-Encoded Features for Algorithm Selection in Mixed-Variable Black-Box Optimization. | Konstantin Dietrich, Raphael Patrick Prager, Carola Doerr, Heike Trautmann |
| 2023 | FOGA | Neural Networks as Black-Box Benchmark Functions Optimized for Exploratory Landscape Features. | Raphael Patrick Prager, Konstantin Dietrich, Lennart Schneider, Lennart Schpermeier, Bernd Bischl, Pascal Kerschke, Heike Trautmann, Olaf Mersmann |
| 2023 | GECCO | Investigating the Viability of Existing Exploratory Landscape Analysis Features for Mixed-Integer Problems. | Raphael Patrick Prager, Heike Trautmann |
| 2022 | GECCO | A collection of deep learning-based feature-free approaches for characterizing single-objective continuous fitness landscapes. | Moritz Vinzent Seiler, Raphael Patrick Prager, Pascal Kerschke, Heike Trautmann |
| 2022 | PPSN | Automated Algorithm Selection in Single-Objective Continuous Optimization: A Comparative Study of Deep Learning and Landscape Analysis Methods. | Raphael Patrick Prager, Moritz Vinzent Seiler, Heike Trautmann, Pascal Kerschke |
| 2022 | PPSN | HPO ˟ ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis. | Lennart Schneider, Lennart Schpermeier, Raphael Patrick Prager, Bernd Bischl, Heike Trautmann, Pascal Kerschke |