Consensus Clustering Using kNN Mode Seeking. - Jonas Nordhaug Myhre; Karl Øyvind Mikalsen; Sigurd Løkse; Robert Jenssen (SCIA, 2015)

Deep divergence-based clustering. - Michael Kampffmeyer; Sigurd Løkse; Filippo Maria Bianchi; Lorenzo Livi; Arnt-Børre Salberg; Robert Jenssen (MLSP, 2017)

Deep Kernelized Autoencoders. - Michael Kampffmeyer; Sigurd Løkse; Filippo Maria Bianchi; Robert Jenssen; Lorenzo Livi (SCIA (1), 2017)

Spectral Clustering Using PCKID - A Probabilistic Cluster Kernel for Incomplete Data. - Sigurd Løkse; Filippo Maria Bianchi; Arnt-Børre Salberg; Robert Jenssen (SCIA (1), 2017)

Training Echo State Networks with Regularization Through Dimensionality Reduction. - Sigurd Løkse; Filippo Maria Bianchi; Robert Jenssen (Cogn. Comput., 2017)

Bidirectional deep echo state networks. - Filippo Maria Bianchi; Simone Scardapane; Sigurd Løkse; Robert Jenssen (CoRR, 2017)

Bidirectional deep-readout echo state networks. - Filippo Maria Bianchi; Simone Scardapane; Sigurd Løkse; Robert Jenssen (ESANN, 2018)

Ranking Using Transition Probabilities Learned from Multi-Attribute Data. - Sigurd Løkse; Robert Jenssen (ICASSP, 2018)

The deep kernelized autoencoder. - Michael Kampffmeyer; Sigurd Løkse; Filippo Maria Bianchi; Robert Jenssen; Lorenzo Livi (Appl. Soft Comput., 2018)

Robust clustering using a kNN mode seeking ensemble. - Jonas Nordhaug Myhre; Karl Øyvind Mikalsen; Sigurd Løkse; Robert Jenssen (Pattern Recognit., 2018)

Information Plane Analysis of Deep Neural Networks via Matrix-Based Renyi's Entropy and Tensor Kernels. - Kristoffer Wickstrøm; Sigurd Løkse; Michael Kampffmeyer; Shujian Yu; José C. Príncipe; Robert Jenssen (CoRR, 2019)

Deep divergence-based approach to clustering. - Michael Kampffmeyer; Sigurd Løkse; Filippo Maria Bianchi; Lorenzo Livi; Arnt-Børre Salberg; Robert Jenssen (Neural Networks, 2019)

SEN: A Novel Feature Normalization Dissimilarity Measure for Prototypical Few-Shot Learning Networks. - Van Nhan Nguyen; Sigurd Løkse; Kristoffer Wickstrøm; Michael Kampffmeyer; Davide Roverso; Robert Jenssen (ECCV (23), 2020)

Reconsidering Representation Alignment for Multi-View Clustering. - Daniel J. Trosten; Sigurd Løkse; Robert Jenssen; Michael Kampffmeyer (CVPR, 2021)

RELAX: Representation Learning Explainability. - Kristoffer K. Wickstrøm; Daniel J. Trosten; Sigurd Løkse; Karl Øyvind Mikalsen; Michael C. Kampffmeyer; Robert Jenssen (CoRR, 2021)

Reservoir Computing Approaches for Representation and Classification of Multivariate Time Series. - Filippo Maria Bianchi; Simone Scardapane; Sigurd Løkse; Robert Jenssen (IEEE Trans. Neural Networks Learn. Syst., 2021)

The Kernelized Taylor Diagram. - Kristoffer Wickstrøm; Juan Emmanuel Johnson; Sigurd Løkse; Gustau Camps-Valls; Karl Øyvind Mikalsen; Michael Kampffmeyer; Robert Jenssen (NAIS, 2022)

Hubs and Hyperspheres: Reducing Hubness and Improving Transductive Few-Shot Learning with Hyperspherical Embeddings. - Daniel J. Trosten; Rwiddhi Chakraborty; Sigurd Løkse; Kristoffer Knutsen Wickstrøm; Robert Jenssen; Michael C. Kampffmeyer (CVPR, 2023)

On the Effects of Self-supervision and Contrastive Alignment in Deep Multi-view Clustering. - Daniel J. Trosten; Sigurd Løkse; Robert Jenssen; Michael C. Kampffmeyer (CVPR, 2023)

Analysis of Deep Convolutional Neural Networks Using Tensor Kernels and Matrix-Based Entropy. - Kristoffer K. Wickstrøm; Sigurd Løkse; Michael C. Kampffmeyer; Shujian Yu; José C. Príncipe; Robert Jenssen (Entropy, 2023)

RELAX: Representation Learning Explainability. - Kristoffer K. Wickstrøm; Daniel J. Trosten; Sigurd Løkse; Ahcène Boubekki; Karl Øyvind Mikalsen; Michael C. Kampffmeyer; Robert Jenssen (Int. J. Comput. Vis., 2023)

Cauchy-Schwarz Divergence Information Bottleneck for Regression. - Shujian Yu; Xi Yu; Sigurd Løkse; Robert Jenssen; José C. Príncipe (ICLR, 2024)

Leveraging tensor kernels to reduce objective function mismatch in deep clustering. - Daniel J. Trosten; Sigurd Løkse; Robert Jenssen; Michael Kampffmeyer (Pattern Recognit., 2024)

The Conditional Cauchy-Schwarz Divergence With Applications to Time-Series Data and Sequential Decision Making. - Shujian Yu; Hongming Li; Sigurd Løkse; Robert Jenssen; José C. Príncipe (IEEE Trans. Pattern Anal. Mach. Intell., 2025)