| Deep learning with convolutional neural networks for EEG decoding and visualization RT Schirrmeister, JT Springenberg, LDJ Fiederer, M Glasstetter, ... Human brain mapping, 2017 | 4121 | 2017 |
| Efficient and Robust Automated Machine Learning M Feurer, A Klein, K Eggensperger, J Springenberg, M Blum, F Hutter Advances in Neural Information Processing Systems (NeurIPS), 2962-2970, 2015 | 3591 | 2015 |
| Auto-sklearn 2.0: Hands-free automl via meta-learning M Feurer, K Eggensperger, S Falkner, M Lindauer, F Hutter The Journal of Machine Learning Research (JMLR) 23 (1), 11936-11996, 2022 | 747* | 2022 |
| SMAC3: A versatile Bayesian optimization package for hyperparameter optimization M Lindauer, K Eggensperger, M Feurer, A Biedenkapp, D Deng, ... The Journal of Machine Learning Research (JMLR) 23 (1), 2475-2483, 2022 | 708* | 2022 |
| TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second N Hollmann, S Müller, K Eggensperger, F Hutter International Conference on Learning Representations (ICLR'23), 2023 | 657 | 2023 |
| Towards an empirical foundation for assessing Bayesian optimization of hyperparameters K Eggensperger, M Feurer, F Hutter, J Bergstra, J Snoek, H Hoos, ... BayesOpt @ NeurIPS 10, 2013 | 532 | 2013 |
| Efficient benchmarking of hyperparameter optimizers via surrogates K Eggensperger, F Hutter, HH Hoos, K Leyton-brown AAAI Conference on Artificial Intelligence (AAAI), 1114-1120, 2015 | 206* | 2015 |
| Practical Automated Machine Learning for the AutoML Challenge 2018 M Feurer, K Eggensperger, S Falkner, M Lindauer, F Hutter AutoML @ ICML, 2018 | 136 | 2018 |
| HPOBench: A Collection of Reproducible Multi-Fidelity Benchmark Problems for HPO K Eggensperger, P Müller, N Mallik, M Feurer, R Sass, A Klein, N Awad, ... Neural Information Processing Systems Track on Datasets and Benchmarks (NeurIPS), 2021 | 131 | 2021 |
| Pitfalls and Best Practices in Algorithm Configuration K Eggensperger, M Lindauer, F Hutter Journal of Artificial Intelligence Research (JAIR) 64, 861-893, 2019 | 91 | 2019 |
| Efficient Benchmarking of Algorithm Configurators via Model-based Surrogates K Eggensperger, M Lindauer, HH Hoos, F Hutter, K Leyton-Brown Machine Learning 101 (1), 15-41, 2018 | 80 | 2018 |
| Efficient Parameter Importance Analysis via Ablation with Surrogates A Biedenkapp, M Lindauer, K Eggensperger, F Hutter, C Fawcett, ... AAAI Conference on Artificial Intelligence (AAAI), 2017 | 74 | 2017 |
| Boah: A tool suite for multi-fidelity bayesian optimization & analysis of hyperparameters M Lindauer, K Eggensperger, M Feurer, A Biedenkapp, J Marben, ... arXiv preprint arXiv:1908.06756, 2019 | 66 | 2019 |
| 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 (JAIR) 79, 639-677, 2024 | 43 | 2024 |
| Position: Why We Must Rethink Empirical Research in Machine Learning M Herrmann, FJD Lange, K Eggensperger, G Casalicchio, M Wever, ... International Conference on Machine Learning (ICML), 2024 | 41 | 2024 |
| Neural Networks for Predicting Algorithm Runtime Distributions K Eggensperger, M Lindauer, F Hutter International Joint Conference on Artificial Intelligence (IJCAI), 2018 | 40 | 2018 |
| Towards assessing the impact of bayesian optimization's own hyperparameters M Lindauer, M Feurer, K Eggensperger, A Biedenkapp, F Hutter DSO workshop @ IJCAI, 2019 | 25 | 2019 |
| Automatic Bone Parameter Estimation for Skeleton Tracking in Optical Motion Capture T Schubert, K Eggensperger, A Gkogkidis, F Hutter, T Ball, W Burgard IEEE International Conference on Robotics and Automation (ICRA), 2016 | 19 | 2016 |
| Towards Quantifying the Effect of Datasets for Benchmarking: A Look at Tabular Machine Learning R Kohli, M Feurer, K Eggensperger, B Bischl, F Hutter DMLR@ ICLR, 2024 | 18 | 2024 |
| How can we quantify, explain, and apply the uncertainty of complex soil maps predicted with neural networks? K Rau, K Eggensperger, F Schneider, P Hennig, T Scholten Science of The Total Environment 944, 173720, 2024 | 16 | 2024 |
Frank HutterPrior Labs; ELLIS Institute Tübingen; University of FreiburgVerified email at cs.uni-freiburg.de
