!MDP Playground: Meta-Features in Reinforcement Learning. - Raghu Rajan; Frank Hutter (CoRR, 2019)

On the Importance of Hyperparameter Optimization for Model-based Reinforcement Learning. - Baohe Zhang; Raghu Rajan; Luis Pineda; Nathan O. Lambert; André Biedenkapp; Kurtland Chua; Frank Hutter; Roberto Calandra (AISTATS, 2021)

TempoRL: Learning When to Act. - André Biedenkapp; Raghu Rajan; Frank Hutter; Marius Lindauer (ICML, 2021)

T3VIP: Transformation-based 3D Video Prediction. - Iman Nematollahi; Erick Rosete-Beas; Seyed Mahdi B. Azad; Raghu Rajan; Frank Hutter; Wolfram Burgard (IROS, 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)

MDP Playground: An Analysis and Debug Testbed for Reinforcement Learning. - Raghu Rajan; Jessica Lizeth Borja Diaz; Suresh Guttikonda; Fabio Ferreira; André Biedenkapp; Jan Ole von Hartz; Frank Hutter (J. Artif. Intell. Res., 2023)

Dreaming of Many Worlds: Learning Contextual World Models aids Zero-Shot Generalization. - Sai Prasanna; Karim Farid; Raghu Rajan; André Biedenkapp (RLJ, 2024)

One-shot World Models Using a Transformer Trained on a Synthetic Prior. - Fabio Ferreira; Moreno Schlageter; Raghu Rajan; Andre Biedenkapp; Frank Hutter (CoRR, 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)

Meta-learning Population-based Methods for Reinforcement Learning. - Johannes Hog; Raghu Rajan; André Biedenkapp; Noor H. Awad; Frank Hutter; Vu Nguyen (Trans. Mach. Learn. Res., 2025)