| Training echo state networks with regularization through dimensionality reduction S Løkse, FM Bianchi, R Jenssen Cognitive Computation 9 (3), 364-378, 2017 | 40 | 2017 |
| Robust clustering using a kNN mode seeking ensemble JN Myhre, KØ Mikalsen, S Løkse, R Jenssen Pattern Recognition 76, 491-505, 2018 | 26 | 2018 |
| Reservoir computing approaches for representation and classification of multivariate time series FM Bianchi, S Scardapane, S Løkse, R Jenssen arXiv preprint arXiv:1803.07870, 2018 | 20 | 2018 |
| Deep kernelized autoencoders M Kampffmeyer, S Løkse, FM Bianchi, R Jenssen, L Livi Scandinavian Conference on Image Analysis, 419-430, 2017 | 17 | 2017 |
| Bidirectional deep-readout echo state networks FM Bianchi, S Scardapane, S Løkse, R Jenssen arXiv preprint arXiv:1711.06509, 2017 | 10 | 2017 |
| Deep divergence-based approach to clustering M Kampffmeyer, S Løkse, FM Bianchi, L Livi, AB Salberg, R Jenssen Neural Networks, 2019 | 7 | 2019 |
| Spectral Clustering Using PCKID – A Probabilistic Cluster Kernel for Incomplete Data S Løkse, FM Bianchi, AB Salberg, R Jenssen Scandinavian Conference on Image Analysis, 431-442, 2017 | 6 | 2017 |
| Consensus clustering using kNN mode seeking JN Myhre, KØ Mikalsen, S Løkse, R Jenssen Scandinavian Conference on Image Analysis, 175-186, 2015 | 6 | 2015 |
| The deep kernelized autoencoder M Kampffmeyer, S Løkse, FM Bianchi, R Jenssen, L Livi Applied Soft Computing 71, 816-825, 2018 | 4 | 2018 |
| Joint ranking and clustering based on Markov Chain transition probabilities learned from data S Løkse UiT Norges arktiske universitet, 2014 | 1 | 2014 |
