| Deepcave: An interactive analysis tool for automated machine learning R Sass, E Bergman, A Biedenkapp, F Hutter, M Lindauer arXiv preprint arXiv:2206.03493, 2022 | 12 | 2022 |
| Can fairness be automated? Guidelines and opportunities for fairness-aware AutoML H Weerts, F Pfisterer, M Feurer, K Eggensperger, E Bergman, N Awad, ... Journal of Artificial Intelligence Research 79, 639-677, 2024 | 8 | 2024 |
| PriorBand: Practical Hyperparameter Optimization in the Age of Deep Learning N Mallik, E Bergman, C Hvarfner, D Stoll, M Janowski, M Lindauer, ... NeurIPS 2023, 2023 | 7* | 2023 |
| Siamese Meta-Learning and Algorithm Selection with'Algorithm-Performance Personas'[Proposal] J Beel, B Tyrell, E Bergman, A Collins, S Nagoor arXiv preprint arXiv:2006.12328, 2020 | 4 | 2020 |
| Algorithm-performance personas ‘for Siamese meta-learning and automated algorithm selection B Tyrrell, E Bergman, GJ Jones, J Beel 7th ICML Workshop on Automated Machine Learning, 2020 | 3 | 2020 |
| Mind the gap: Measuring generalization performance across multiple objectives M Feurer, K Eggensperger, E Bergman, F Pfisterer, B Bischl, F Hutter International Symposium on Intelligent Data Analysis, 130-142, 2023 | 2 | 2023 |
| In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization H Rakotoarison, S Adriaensen, N Mallik, S Garibov, E Bergman, F Hutter arXiv preprint arXiv:2404.16795, 2024 | | 2024 |
| Fast Benchmarking of Asynchronous Multi-Fidelity Optimization on Zero-Cost Benchmarks S Watanabe, N Mallik, E Bergman, F Hutter arXiv preprint arXiv:2403.01888, 2024 | | 2024 |
| Online Neural Architecture Search (ONAS): Adapting neural network architecture search in a continuously evolving domain.[Proposal] N Buskulic, E Bergman, J Beel OSF, 0 | | |
