| Time series cluster kernel for learning similarities between multivariate time series with missing data KØ Mikalsen, FM Bianchi, C Soguero-Ruiz, R Jenssen Pattern Recognition 76, 569-581, 2018 | 53 | 2018 |
| Analysis of free text in electronic health records for identification of cancer patient trajectories K Jensen, C Soguero-Ruiz, KO Mikalsen, RO Lindsetmo, ... Scientific reports 7, 46226, 2017 | 42 | 2017 |
| Robust clustering using a kNN mode seeking ensemble JN Myhre, KØ Mikalsen, S Løkse, R Jenssen Pattern Recognition 76, 491-505, 2018 | 20 | 2018 |
| Classification of postoperative surgical site infections from blood measurements with missing data using recurrent neural networks AS Strauman, FM Bianchi, KØ Mikalsen, M Kampffmeyer, C Soguero-Ruiz, ... 2018 IEEE EMBS International Conference on Biomedical & Health Informatics …, 2018 | 13 | 2018 |
| Using anchors from free text in electronic health records to diagnose postoperative delirium KØ Mikalsen, C Soguero-Ruiz, K Jensen, K Hindberg, M Gran, ... Computer Methods and Programs in Biomedicine 152, 105-114, 2017 | 10 | 2017 |
| Noisy multi-label semi-supervised dimensionality reduction KØ Mikalsen, C Soguero-Ruiz, FM Bianchi, R Jenssen Pattern Recognition 90, 257-270, 2019 | 8 | 2019 |
| Maximizing Interpretability and Cost-Effectiveness of Surgical Site Infection (SSI) Predictive Models Using Feature-Specific Regularized Logistic Regression on Preoperative … P Kocbek, N Fijacko, C Soguero-Ruiz, KØ Mikalsen, U Maver, ... Computational and Mathematical Methods in Medicine 2019, 2019 | 7 | 2019 |
| Learning representations for multivariate time series with missing data using Temporal Kernelized Autoencoders FM Bianchi, L Livi, KØ Mikalsen, M Kampffmeyer, R Jenssen arXiv preprint arXiv:1805.03473, 2018 | 7 | 2018 |
| Learning similarities between irregularly sampled short multivariate time series from EHRs KØ Mikalsen, FM Bianchi, C Soguero-Ruiz, SO Skrøvseth, RO Lindsetmo, ... | 7 | 2016 |
| Learning representations of multivariate time series with missing data FM Bianchi, L Livi, KØ Mikalsen, M Kampffmeyer, R Jenssen Pattern Recognition 96, 106973, 2019 | 6 | 2019 |
| Consensus clustering using knn mode seeking JN Myhre, KØ Mikalsen, S Løkse, R Jenssen Scandinavian Conference on Image Analysis, 175-186, 2015 | 6 | 2015 |
| An Unsupervised Multivariate Time Series Kernel Approach for Identifying Patients with Surgical Site Infection from Blood Samples KØ Mikalsen, C Soguero-Ruiz, FM Bianchi, A Revhaug, R Jenssen arXiv preprint arXiv:1803.07879, 2018 | 5 | 2018 |
| Learning compressed representations of blood samples time series with missing data FM Bianchi, KØ Mikalsen, R Jenssen arXiv preprint arXiv:1710.07547, 2017 | 4 | 2017 |
| Deforming the vacuum. On the physical origin and numerical calculation of the Casimir effect. KØ Mikalsen UiT Norges arktiske universitet, 2014 | 1 | 2014 |
| A Kernel to Exploit Informative Missingness in Multivariate Time Series from EHRs KØ Mikalsen, C Soguero-Ruiz, R Jenssen arXiv preprint arXiv:2002.12359, 2020 | | 2020 |
| Time series cluster kernels to exploit informative missingness and incomplete label information KØ Mikalsen, C Soguero-Ruiz, FM Bianchi, A Revhaug, R Jenssen arXiv preprint arXiv:1907.05251, 2019 | | 2019 |
| Advancing Unsupervised and Weakly Supervised Learning with Emphasis on Data-Driven Healthcare KØ Mikalsen UiT Norges arktiske universitet, 2019 | | 2019 |
| Using multi-anchors to identify patients suffering from multimorbidities K yvind Mikalsen, C Soguero-Ruiz, I Mora-Jimenez, ICL Fando, ... 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2018 | | 2018 |
| Towards deep anchor learning MA Hansen, KØ Mikalsen, M Kampffmeyer, C Soguero-Ruiz, R Jenssen 2018 IEEE EMBS International Conference on Biomedical & Health Informatics …, 2018 | | 2018 |
| The time series cluster kernel KØ Mikalsen, FM Bianchi, C Soguero-Ruiz, R Jenssen 2017 IEEE 27th International Workshop on Machine Learning for Signal …, 2017 | | 2017 |
Robert JenssenProfessor & Head, Machine Learning Group, Department of Physics and Technology, University ofVerifisert e-postadresse på uit.no
