Raghu Rajan

According to our database, Raghu Rajan authored at least 15 papers between 2019 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Beyond Self-Play and Scale: A Behavior Benchmark for Generalization in Autonomous Driving.

Aron Distelzweig, Faris Janjos, Andreas Look, Anna Rothenhäusler, Daniel Jost, Oliver Scheel, Raghu Rajan, Daphne Cornelisse, Eugene Vinitsky, Joschka Boedecker

CoRR, May, 2026

Super Agents and Confounders: Influence of surrounding agents on vehicle trajectory prediction.

Daniel Jost, Luca Paparusso, Martin Stoll, Jörg Wagner, Raghu Rajan, Joschka Bödecker

CoRR, April, 2026

Don't double it: Efficient Agent Prediction in Occlusions.

Anna Rothenhäusler, Markus Mazzola, Andreas Look, Raghu Rajan, Joschka Bödecker

CoRR, January, 2026

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 Hoos, Marius Lindauer, Theresa Eimer

J. Data-centric Mach. Learn. Res., 2026

2025

Perfect Prediction or Plenty of Proposals? What Matters Most in Planning for Autonomous Driving.

Aron Distelzweig, Faris Janjos, Oliver Scheel, Sirish Reddy Varra, Raghu Rajan, Joschka Boedecker

CoRR, October, 2025

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

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

One-shot World Models Using a Transformer Trained on a Synthetic Prior.

Fabio Ferreira, Moreno Schlageter, Raghu Rajan, Andre Biedenkapp, Frank Hutter

CoRR, 2024

Dreaming of Many Worlds: Learning Contextual World Models aids Zero-Shot Generalization.

Sai Prasanna, Karim Farid, Raghu Rajan, André Biedenkapp

RLJ, 2024

2023

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

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

T3VIP: Transformation-based 3D Video Prediction.

Iman Nematollahi, Erick Rosete-Beas, Seyed Mahdi B. Azad, Raghu Rajan, Frank Hutter, Wolfram Burgard

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

2021

TempoRL: Learning When to Act.

André Biedenkapp, Raghu Rajan, Frank Hutter, Marius Lindauer

Proceedings of the 38th International Conference on Machine Learning, 2021

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

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2019

!MDP Playground: Meta-Features in Reinforcement Learning.

Raghu Rajan, Frank Hutter

CoRR, 2019