| Big universe, big data: Machine learning and image analysis for astronomy J Kremer, K Stensbo-Smidt, F Gieseke, KS Pedersen, C Igel IEEE Intelligent Systems 32 (2), 16-22, 2017 | 119 | 2017 |
| Shape index descriptors applied to texture-based galaxy analysis KS Pedersen, K Stensbo-Smidt, A Zirm, C Igel Proceedings of the IEEE International Conference on Computer Vision, 2440-2447, 2013 | 17 | 2013 |
| Nearest neighbour regression outperforms model-based prediction of specific star formation rate K Stensbo-Smidt, C Igel, A Zirm, KS Pedersen 2013 IEEE international conference on big data, 141-144, 2013 | 15 | 2013 |
| Sacrificing information for the greater good: how to select photometric bands for optimal accuracy K Stensbo-Smidt, F Gieseke, C Igel, A Zirm, K Steenstrup Pedersen Monthly Notices of the Royal Astronomical Society 464 (3), 2577-2596, 2017 | 13 | 2017 |
| Simple, fast and accurate photometric estimation of specific star formation rate K Stensbo-Smidt MNRAS 464 (3), 2577-2596, 2016 | 8 | 2016 |
| Adaptive Cholesky Gaussian Processes S Bartels, K Stensbo-Smidt, P Moreno-Muņoz, W Boomsma, J Frellsen, ... International Conference on Artificial Intelligence and Statistics, 408-452, 2023 | 1 | 2023 |
| Implicit Variational Inference for High-Dimensional Posteriors A Uppal, K Stensbo-Smidt, WK Boomsma, J Frellsen arXiv preprint arXiv:2310.06643, 2023 | | 2023 |
| Recycling on a cosmic scale, extracting new information from old data sets K Stensbo-Smidt Ph. D. Thesis, 2017 | | 2017 |
| Recycling on a Cosmic Scale K Stensbo-Smidt, KS Pedersen, C Igel | | 2016 |
| The Perceptron Algorithm K Stensbo-Smidt | | 2015 |
