| SMAC3: A versatile Bayesian optimization package for hyperparameter optimization M Lindauer, K Eggensperger, M Feurer, A Biedenkapp, D Deng, ... Journal of Machine Learning Research 23 (54), 1-9, 2022 | 599 | 2022 |
| Contextualize Me--The Case for Context in Reinforcement Learning C Benjamins, T Eimer, F Schubert, A Mohan, S Döhler, A Biedenkapp, ... Trans. Mach. Learn. Res., 2023 | 71 | 2023 |
| CARL: A benchmark for contextual and adaptive reinforcement learning C Benjamins, T Eimer, F Schubert, A Biedenkapp, B Rosenhahn, F Hutter, ... Workshop on Ecological Theory of Reinforcement Learning, NeurIPS 2021, 2021 | 32 | 2021 |
| AutoRL Hyperparameter Landscapes A Mohan, C Benjamins, K Wienecke, A Dockhorn, M Lindauer International Conference on Automated Machine Learning, 2023 | 18 | 2023 |
| PI is back! Switching Acquisition Functions in Bayesian Optimization C Benjamins, E Raponi, A Jankovic, K van der Blom, ML Santoni, ... NeurIPS Workshop on Gaussian Processes, Spatiotemporal Modeling, and …, 2022 | 16 | 2022 |
| Application of machine learning for fleet-based condition monitoring of ball screw drives in machine tools B Denkena, MA Dittrich, H Noske, D Lange, C Benjamins, M Lindauer The International Journal of Advanced Manufacturing Technology 127 (3), 1143 …, 2023 | 10 | 2023 |
| Self-Adjusting Weighted Expected Improvement for Bayesian Optimization C Benjamins, E Raponi, A Jankovic, C Doerr, M Lindauer International Conference on Automated Machine Learning, 2023 | 10 | 2023 |
| Towards Automated Design of Bayesian Optimization via Exploratory Landscape Analysis C Benjamins, A Jankovic, E Raponi, K van der Blom, M Lindauer, C Doerr Companion Proceedings of the Conference on Genetic and Evolutionary …, 2022 | 10 | 2022 |
| MO-SMAC: Multiobjective Sequential Model-Based Algorithm Configuration JG Rook, C Benjamins, J Bossek, H Trautmann, HH Hoos, M Lindauer Evolutionary Computation, 1-24, 2025 | 7 | 2025 |
| Hyperparameters in Contextual RL are Highly Situational T Eimer, C Benjamins, M Lindauer NeurIPS 2021 Workshop on Ecological Theory of Reinforcement Learning, 2021 | 7 | 2021 |
| Instance Selection for Dynamic Algorithm Configuration with Reinforcement Learning: Improving Generalization C Benjamins, G Cenikj, A Nikolikj, A Mohan, T Eftimov, M Lindauer Proceedings of the Genetic and Evolutionary Computation Conference Companion …, 2024 | 6 | 2024 |
| carps: A framework for comparing n hyperparameter optimizers on m benchmarks C Benjamins, H Graf, S Segel, D Deng, T Ruhkopf, L Hennig, S Basu, ... arXiv preprint arXiv:2506.06143, 2025 | 5 | 2025 |
| POLTER: Policy Trajectory Ensemble Regularization for Unsupervised Reinforcement Learning F Schubert, C Benjamins, S Döhler, B Rosenhahn, M Lindauer Trans. Mach. Learn. Res., 2022 | 5 | 2022 |
| Bayesian Optimisation for Protein Sequence Design: Gaussian Processes with Zero-Shot Protein Language Model Prior Mean C Benjamins, S Surana, O Bent, M Lindauer, P Duckworth Machine Learning in Structural Biology Workshop at NeurIPS 2024, 4, 2024 | 3 | 2024 |
| Towards Self-Adjusting Weighted Expected Improvement for Bayesian Optimization C Benjamins, E Raponi, A Jankovic, C Doerr, M Lindauer GECCO'23 Companion: Companion Conference on Genetic and Evolutionary …, 2023 | 2 | 2023 |
| SynthACticBench: A Capability-Based Synthetic Benchmark for Algorithm Configuration V Margraf, A Lappe, M Wever, C Benjamins, E Hüllermeier, M Lindauer Proceedings of the Genetic and Evolutionary Computation Conference, 39-47, 2025 | 1 | 2025 |
| ARLBench: Flexible and Efficient Benchmarking for Hyperparameter Optimization in Reinforcement Learning J Becktepe, J Dierkes, C Benjamins, A Mohan, D Salinas, R Rajan, ... arXiv preprint arXiv:2409.18827, 2024 | 1 | 2024 |
| Mighty: A Comprehensive Tool for studying Generalization, Meta-RL and AutoRL A Mohan, T Eimer, C Benjamins, M Lindauer, A Biedenkapp Eighteenth European Workshop on Reinforcement Learning, 2025 | | 2025 |
| Bayesian Optimization for Protein Sequence Design: Back to Simplicity with Gaussian Processes C Benjamins, S Surana, O Bent, M Lindauer, P Duckworth AI for Accelerated Materials Design-NeurIPS 2024, 2024 | | 2024 |
| Understanding AutoRL Hyperparameter Landscapes A Mohan, C Benjamins, K Wienecke, A Dockhorn, M Lindauer | | |
Marius LindauerLeibniz University Hannover (Germany), Institute of Artificial Intelligence LUH|AI, L3S ResearchVerified email at ai.uni-hannover.de
