Dynamic Algorithm Configuration: Foundation of a New Meta-Algorithmic Framework. - André Biedenkapp; H. Furkan Bozkurt; Theresa Eimer; Frank Hutter; Marius Lindauer (ECAI, 2020)

Self-Paced Context Evaluation for Contextual Reinforcement Learning. - Theresa Eimer; André Biedenkapp; Frank Hutter; Marius Lindauer (ICML, 2021)

DACBench: A Benchmark Library for Dynamic Algorithm Configuration. - Theresa Eimer; André Biedenkapp; Maximilian Reimer; Steven Adriaensen; Frank Hutter; Marius Lindauer (IJCAI, 2021)

Automatic Risk Adaptation in Distributional Reinforcement Learning. - Frederik Schubert; Theresa Eimer; Bodo Rosenhahn; Marius Lindauer (CoRR, 2021)

CARL: A Benchmark for Contextual and Adaptive Reinforcement Learning. - Carolin Benjamins; Theresa Eimer; Frederik Schubert; André Biedenkapp; Bodo Rosenhahn; Frank Hutter; Marius Lindauer (CoRR, 2021)

Contextualize Me - The Case for Context in Reinforcement Learning. - Carolin Benjamins; Theresa Eimer; Frederik Schubert; Aditya Mohan; André Biedenkapp; Bodo Rosenhahn; Frank Hutter; Marius Lindauer (CoRR, 2022)

Hyperparameters in Contextual RL are Highly Situational. - Theresa Eimer; Carolin Benjamins; Marius Lindauer (CoRR, 2022)

Automated Dynamic Algorithm Configuration. - Steven Adriaensen; André Biedenkapp; Gresa Shala; Noor H. Awad; Theresa Eimer; Marius Lindauer; Frank Hutter (J. Artif. Intell. Res., 2022)

Automated Reinforcement Learning (AutoRL): A Survey and Open Problems. - Jack Parker-Holder; Raghu Rajan; Xingyou Song; André Biedenkapp; Yingjie Miao; Theresa Eimer; Baohe Zhang; Vu Nguyen; Roberto Calandra; Aleksandra Faust; Frank Hutter; Marius Lindauer (J. Artif. Intell. Res., 2022)

Hyperparameters in Reinforcement Learning and How To Tune Them. - Theresa Eimer; Marius Lindauer; Roberta Raileanu (ICML, 2023)

Contextualize Me - The Case for Context in Reinforcement Learning. - Carolin Benjamins; Theresa Eimer; Frederik Schubert; Aditya Mohan; Sebastian Döhler; André Biedenkapp; Bodo Rosenhahn; Frank Hutter; Marius Lindauer (Trans. Mach. Learn. Res., 2023)

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)

AutoML in the Age of Large Language Models: Current Challenges, Future Opportunities and Risks. - Alexander Tornede; Difan Deng; Theresa Eimer; Joseph Giovanelli; Aditya Mohan; Tim Ruhkopf; Sarah Segel; Daphne Theodorakopoulos; Tanja Tornede; Henning Wachsmuth; Marius Lindauer (Trans. Mach. Learn. Res., 2024)

Task Scheduling & Forgetting in Multi-Task Reinforcement Learning. - Marc Speckmann; Theresa Eimer (CoRR, 2025)

Growing with Experience: Growing Neural Networks in Deep Reinforcement Learning. - Lukas Fehring; Marius Lindauer; Theresa Eimer (CoRR, 2025)

Revisiting Learning Rate Control. - Micha Henheik; Theresa Eimer; Marius Lindauer (CoRR, 2025)