Robust clustering using a kNN mode seeking ensemble JN Myhre, KØ Mikalsen, S Løkse, R Jenssen Pattern Recognition 76, 491-505, 2018 | 54 | 2018 |
Controlling blood glucose levels in patients with type 1 diabetes using fitted q-iterations and functional features JN Myhre, IK Launonen, S Wei, F Godtliebsen 2018 IEEE 28th International Workshop on Machine Learning for Signal …, 2018 | 18 | 2018 |
In-silico evaluation of glucose regulation using policy gradient reinforcement learning for patients with type 1 diabetes mellitus J Nordhaug Myhre, M Tejedor, I Kalervo Launonen, A El Fathi, ... Applied Sciences 10 (18), 6350, 2020 | 15 | 2020 |
Mixture weight influence on kernel entropy component analysis and semi-supervised learning using the lasso JN Myhre, R Jenssen 2012 IEEE International Workshop on Machine Learning for Signal Processing, 1-6, 2012 | 12 | 2012 |
Computationally efficient exact calculation of kernel density derivatives M Shaker, JN Myhre, D Erdogmus Journal of Signal Processing Systems 81, 321-332, 2015 | 6 | 2015 |
Consensus clustering using knn mode seeking JN Myhre, KØ Mikalsen, S Løkse, R Jenssen Image Analysis: 19th Scandinavian Conference, SCIA 2015, Copenhagen, Denmark …, 2015 | 6 | 2015 |
Invertible nonlinear cluster unwrapping M Shaker, JN Myhre, MD Kaba, D Erdogmus 2014 IEEE International Workshop on Machine Learning for Signal Processing …, 2014 | 6 | 2014 |
Simpler is better: Spectral regularization and up-sampling techniques for variational autoencoders S Björk, JN Myhre, TH Johansen ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and …, 2022 | 5 | 2022 |
Clinically relevant features for predicting the severity of surgical site infections A Boubekki, JN Myhre, LT Luppino, KØ Mikalsen, A Revhaug, R Jenssen IEEE Journal of Biomedical and Health Informatics 26 (4), 1794-1801, 2021 | 3 | 2021 |
Semi-supervised Classification using Kernel Entropy Component Analysis and the LASSO. JN Myhre Universitetet i Tromsø, 2011 | 3 | 2011 |
Droner som FKT-bruk av droner som forebyggende tiltak i beitenæringen E Winje, TA Bjørn, I Hansen, E Meisingset, A Haugen, JB Heppelmann, ... NIBIO, 2023 | 2 | 2023 |
Secant manifold constrained random projections-improved cluster ensembles JN Myhre 2018 International Joint Conference on Neural Networks (IJCNN), 1-7, 2018 | 2 | 2018 |
Manifold unwrapping using density ridges JN Myhre, M Shaker, D Kaba, R Jenssen, D Erdogmus arXiv preprint arXiv:1604.01602, 2016 | 2 | 2016 |
Evaluating Deep Q-Learning Algorithms for Controlling Blood Glucose in In Silico Type 1 Diabetes M Tejedor, SN Hjerde, JN Myhre, F Godtliebsen Diagnostics 13 (19), 3150, 2023 | 1 | 2023 |
Variable Depth Bayesian Neural Networks Using Reversible Jumps J Berezowski, TH Johansen, JN Myhre, F Godtliebsen 2022 IEEE 32nd International Workshop on Machine Learning for Signal …, 2022 | 1 | 2022 |
Controlling blood glucose for patients with type 1 DiabetesUsing deep reinforcement learning–The influence OfChanging the reward function MAT Hernandez, JN Myhre Proceedings of the Northern Lights Deep Learning Workshop 1, 6-6, 2020 | 1 | 2020 |
A generic unfolding algorithm for manifolds estimated by local linear approximations JN Myhre, M Shaker, MD Kaba, R Jenssen, D Erdogmus Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 1 | 2020 |
Density ridge manifold traversal JN Myhre, M Kampffmeyer, R Jenssen 2017 IEEE International Conference on Acoustics, Speech and Signal …, 2017 | 1 | 2017 |
Evaluating Deep Q-Learning Algorithms for Controlling Blood Glucose in In Silico Type 1 Diabetes THM Angel, S Hjerde, JN Myhre, F Godtliebsen MDPI, 2023 | | 2023 |
Evaluating Deep Q-Learning Algorithms for Controlling Blood Glucose in In Silico Type 1 Diabetes. Diagnostics 2023, 13, 3150 M Tejedor, SN Hjerde, JN Myhre, F Godtliebsen | | 2023 |