Publications

2024

1. Structure in Deep Reinforcement Learning: A survey and open problems

   Aditya Mohan, Amy Zhang, and Marius Lindauer

   Journal of Artificial Intelligence Research (JAIR), 2024

2023

1. AutoRL Hyperparameter Landscapes

   Aditya Mohan, Carolin Benjamins, Konrad Wienecke, Alexander Dockhorn, and Marius Lindauer

   Proceedings of the Second International Conference on Automated Machine Learning (AutoML), 2023
2. Contextualize Me - The Case for Context in Reinforcement Learning

   Carolin Benjamins, Theresa Eimer, F. Schubert, Aditya Mohan, Andre Biedenkapp, Bodo Rosenhahn, Frank Hutter, and Marius Lindauer

   Transactions on Machine Learning Research (TMLR), 2023
3. Learning Activation Functions for Sparse Neural Networks

   Mohammad Loni, Aditya Mohan, Mehdi Asadi, and Marius Lindauer

   Proceedings of the Second International Conference on Automated Machine Learning (AutoML), 2023
4. MASIF: Meta-learned Algorithm Selection using Implicit Fidelity Information

   Tim Ruhkopf, Aditya Mohan, D. Deng, A. Tornede, F. Hutter, and Marius Lindauer

   Transactions on Machine Learning Research (TMLR), 2023
5. 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, and Marius Lindauer

   arXiv preprint arXiv:2306.08107, 2023

2022

1. Towards Meta-learned Algorithm Selection using Implicit Fidelity Information

   Aditya Mohan, Tim Ruhkopf, and Marius Lindauer

   ICML 2022 Workshop Adaptive Experimental Design and Active Learning in the Real World (ReALML), 2022