Efficient Use of Large Pre-Trained Models for Low Resource ASR. - Peter Vieting; Christoph Lüscher; Julian Dierkes; Ralf Schlüter; Hermann Ney (CoRR, 2022)

Efficient Utilization of Large Pre-Trained Models for Low Resource ASR. - Peter Vieting; Christoph Lüscher; Julian Dierkes; Ralf Schlüter; Hermann Ney (ICASSP Workshops, 2023)

Combining Automated Optimisation of Hyperparameters and Reward Shape. - Julian Dierkes; Emma Cramer; Holger H. Hoos; Sebastian Trimpe (RLJ, 2024)

ARLBench: Flexible and Efficient Benchmarking for Hyperparameter Optimization in Reinforcement Learning. - Jannis Becktepe; Julian Dierkes; Carolin Benjamins; Aditya Mohan; David Salinas; Raghu Rajan; Frank Hutter; Holger H. Hoos; Marius Lindauer; Theresa Eimer (CoRR, 2024)

TinyverseGP: Towards a Modular Cross-domain Benchmarking Framework for Genetic Programming. - Roman Kalkreuth; Fabrício Olivetti de França; Julian Dierkes; Marie Anastacio; Anja Jankovic 003; Zdenek Vasícek; Holger H. Hoos (CoRR, 2025)