An Ontology-Based Concept for Meta AutoML. - Bernhard G. Humm; Alexander Zender (AIAI, 2021)

Ontology-based Meta AutoML. - Alexander Zender; Bernhard G. Humm (Integr. Comput. Aided Eng., 2022)

Towards Improved User Experience for Artificial Intelligence Systems. - Lisa Brand; Bernhard G. Humm; Andrea Krajewski; Alexander Zender (EANN, 2023)

Improving the Efficiency of Meta AutoML via Rule-based Training Strategies. - Alexander Zender; Bernhard G. Humm; Tim Pachmann (FedCSIS, 2023)

Detecting Spells in Fantasy Literature with a Transformer Based Artificial Intelligence. - Marcel Moravek; Alexander Zender; Andreas Müller (CoRR, 2023)

New directions for applied knowledge-based AI and machine learning. - Bernhard G. Humm; Phil Archer; Hermann Bense; Carolynn Bernier; Christian Goetz; Thomas Hoppe 001; Fabienne Schumann; Melanie Siegel; Rigo Wenning; Alexander Zender (Inform. Spektrum, 2023)

Benchmarking Meta AutoML. - Alexander Zender; Bernhard G. Humm (CENTERIS/ProjMAN/HCist, 2024)

Successfully Improving the User Experience of an Artificial Intelligence System. - Alexander Zender; Bernhard G. Humm; Anna Holzheuser (FedCSIS, 2024)

Predicting the Optimal Runtime Limit for Meta AutoML. - Alexander Zender; Bernhard G. Humm; Pia Charline Friehe (ICAAI, 2024)

New trends in applied machine intelligence. - Bernhard G. Humm; Lothar B. Blum; Johannes Busse; Sophie Decher; Michael Dembach; Christian Goetz; Thomas Hoppe 001; Lukas Kaupp; Anne Schwerk; Eva Seidlmayer; Melanie Siegel; Rigo Wenning; et al. (Inform. Spektrum, 2025)