| Developing and validating COVID-19 adverse outcome risk prediction models from a bi-national European cohort of 5594 patients E Jimenez-Solem, TS Petersen, C Hansen, C Hansen, C Lioma, C Igel, ... Scientific reports 11 (1), 3246, 2021 | 81 | 2021 |
| Second order PAC-Bayesian bounds for the weighted majority vote A Masegosa, S Lorenzen, C Igel, Y Seldin Advances in Neural Information Processing Systems 33, 5263-5273, 2020 | 40 | 2020 |
| Tracking behavioral patterns among students in an online educational system S Lorenzen, N Hjuler, S Alstrup arXiv preprint arXiv:1908.08937, 2019 | 20 | 2019 |
| Using machine learning for predicting intensive care unit resource use during the COVID-19 pandemic in Denmark SS Lorenzen, M Nielsen, E Jimenez-Solem, TS Petersen, A Perner, ... Scientific reports 11 (1), 18959, 2021 | 17 | 2021 |
| On PAC-Bayesian bounds for random forests SS Lorenzen, C Igel, Y Seldin Machine Learning 108 (8), 1503-1522, 2019 | 16 | 2019 |
| Information bottleneck: Exact analysis of (quantized) neural networks SS Lorenzen, C Igel, M Nielsen arXiv preprint arXiv:2106.12912, 2021 | 13 | 2021 |
| Revisiting wedge sampling for budgeted maximum inner product search SS Lorenzen, N Pham Joint European Conference on Machine Learning and Knowledge Discovery in …, 2020 | 12 | 2020 |
| Chebyshev-Cantelli PAC-Bayes-Bennett inequality for the weighted majority vote YS Wu, A Masegosa, S Lorenzen, C Igel, Y Seldin Advances in Neural Information Processing Systems 34, 12625-12636, 2021 | 11 | 2021 |
| On predicting student performance using low-rank matrix factorization techniques S Lorenzen, N Pham, S Alstrup European Conference on e-Learning, 326-334, 2017 | 9 | 2017 |
| Detecting ghostwriters in high schools M Stavngaard, A Sørensen, S Lorenzen, N Hjuler, S Alstrup arXiv preprint arXiv:1906.01635, 2019 | 8 | 2019 |
| DABAI: A data driven project for e-Learning in Denmark S Alstrup, C Hansen, C Hansen, N Hjuler, S Lorenzen, N Pham European Conference on e-Learning, 18-24, 2017 | 6 | 2017 |
| Steiner tree heuristics in Euclidean d-space A Olsen, S Lorenzen, R Fonseca, P Winter Proc. of the 11th DIMACS Implementation Challenge, 2014 | 6 | 2014 |
| Online transfer learning with partial feedback Z Kang, M Nielsen, B Yang, L Deng, SS Lorenzen Expert Systems with Applications 212, 118738, 2023 | 4 | 2023 |
| Investigating writing style development in high school S Lorenzen, N Hjuler, S Alstrup arXiv preprint arXiv:1906.03072, 2019 | 2 | 2019 |
| Assessing the utility of deep neural networks in detecting superficial surgical site infections from free text electronic health record data A Bonde, S Lorenzen, G Brixen, A Troelsen, M Sillesen Frontiers in digital health 5, 1249835, 2024 | 1 | 2024 |
| Steiner Tree Heuristic in the Euclidean d-Space Using Bottleneck Distances SS Lorenzen, P Winter Experimental Algorithms: 15th International Symposium, SEA 2016, St …, 2016 | 1 | 2016 |
| Developing Machine Learning Models for Predicting Intensive Care Unit Resource Use During the COVID-19 Pandemic (preprint) SS Lorenzen, M Nielsen, E Jimenez-Solem, TS Petersen, A Perner, ... | | 2021 |
| Learning from Educational Data SS Lorenzen School of The Faculty of Science, University of Copenhagen, 2019 | | 2019 |
| Bottleneck distances and Steiner trees in the Euclidean d-space P Winter, SS Lorenzen The European Workshop on Computational Geometry (EuroCG) 2016, 2016 | | 2016 |
| Bottleneck Distances and Steiner Trees in the Euclidean d-Space SS Lorenzen, P Winter | | |
