| Probabilistic movement models and zones of control U Brefeld, J Lasek, S Mair Machine Learning 108 (1), 127-147, 2019 | 56 | 2019 |
| Frame-based data factorizations S Mair, A Boubekki, U Brefeld International Conference on Machine Learning, 2305-2313, 2017 | 27 | 2017 |
| Coresets for archetypal analysis S Mair, U Brefeld Advances in Neural Information Processing Systems, 7247-7255, 2019 | 17 | 2019 |
| Distributed robust Gaussian Process regression S Mair, U Brefeld Knowledge and Information Systems 55 (2), 415-435, 2018 | 10 | 2018 |
| Contextual movement models based on normalizing flows SG Fadel, S Mair, R da Silva Torres, U Brefeld AStA Advances in Statistical Analysis 107 (1), 51-72, 2023 | 8 | 2023 |
| Self-supervised Siamese Autoencoders F Baier, S Mair, SG Fadel International Symposium on Intelligent Data Analysis, 117-128, 2024 | 6 | 2024 |
| HyperUCB: Hyperparameter Optimization using Contextual Bandits M Tavakol, S Mair, K Morik Joint European Conference on Machine Learning and Knowledge Discovery in …, 2019 | 5 | 2019 |
| Ising on the Graph: Task-specific Graph Subsampling via the Ising Model M Bånkestad, J Andersson, S Mair, J Sjölund Learning on Graphs, 2024 | 4 | 2024 |
| Universal threshold calculation for fingerprinting decoders using mixture models M Schäfer, S Mair, W Berchtold, M Steinebach Proceedings of the 3rd ACM Workshop on Information Hiding and Multimedia …, 2015 | 4 | 2015 |
| Principled Interpolation in Normalizing Flows SG Fadel, S Mair, R da S. Torres, U Brefeld Machine Learning and Knowledge Discovery in Databases. Research Track …, 2021 | 3 | 2021 |
| Frame-Based Optimal Design S Mair, Y Rudolph, V Closius, U Brefeld Joint European Conference on Machine Learning and Knowledge Discovery in …, 2018 | 2 | 2018 |
| On Feynman-Kac training of partial Bayesian neural networks Z Zhao, S Mair, TB Schön, J Sjölund International Conference on Artificial Intelligence and Statistics, 3223-3231, 2024 | 1 | 2024 |
| Archetypal Analysis++: Rethinking the Initialization Strategy S Mair, J Sjölund Transactions on Machine Learning Research, 2024 | 1 | 2024 |
| Computing efficient data summaries S Mair | 1 | 2022 |
| Personalized Privacy Amplification via Importance Sampling D Fay, S Mair, J Sjölund Transactions on Machine Learning Research, 2025 | | 2025 |
| Explaining the Impact of Training on Vision Models via Activation Clustering A Boubekki, SG Fadel, S Mair arXiv preprint arXiv:2411.19700, 2024 | | 2024 |
| Leveraging Activations for Superpixel Explanations A Boubekki, SG Fadel, S Mair arXiv preprint arXiv:2406.04933, 2024 | | 2024 |
| Efficient radiation treatment planning based on voxel importance S Mair, A Fu, J Sjölund Physics in Medicine and Biology 69, 2024 | | 2024 |
| Towards General Geometries for Embedding Knowledge Graphs SG Fadel, T Paulsen, S Mair ICML 2024 Workshop on Geometry-grounded Representation Learning and …, 2024 | | 2024 |
| Berechnung effizienter Datenzusammenfassungen S Mair Ausgezeichnete Informatikdissertationen 2021, 2022 | | 2022 |
Ulf BrefeldLeuphana Universität LüneburgE-mail megerősítve itt: leuphana.de