Improving competitive differential evolution using automatic programming. - Marius Geitle; Roland Olsson 001 (ICSAI, 2017)

A New Baseline for Automated Hyper-Parameter Optimization. - Marius Geitle; Roland Olsson 001 (LOD, 2019)

Evaluating Population Based Training on Small Datasets. - Frode Tennebø; Marius Geitle (NIK, 2019)

A distributed Front-end Edge node assessment model by using Fuzzy and a learning-to-rank method-machine learning. - Marius Geitle; Amin Shahraki (IEEE DataPort, 2019)

A distributed Fog node assessment model by using Fuzzy rules learned by XGBoost. - Amin Shahraki; Marius Geitle (IEEE DataPort, 2019)

A comparative node evaluation model for highly heterogeneous massive-scale Internet of Things-Mist networks. - Amin Shahraki; Marius Geitle; Øystein Haugen (Trans. Emerg. Telecommun. Technol., 2020)

Exploring the Hyperparameters of XGBoost Through 3D Visualizations. - Ole-Edvard Ørebæk; Marius Geitle (AAAI Spring Symposium: Combining Machine Learning with Knowledge Engineering, 2021)

Deep Ensemble Transformers for Dimensionality Reduction. - Maria Nareklishvili; Marius Geitle (IEEE Trans. Neural Networks Learn. Syst., 2025)