Sigurd Løkse

Publication Activity (10 Years)

Years Active: 2015-2024
Publications (10 Years): 33

Top Topics

Echo State Networks

Top Venues

Pattern Recognit.

Publications

Shujian Yu, Xi Yu, Sigurd Løkse, Robert Jenssen, José C. Príncipe
Cauchy-Schwarz Divergence Information Bottleneck for Regression. ICLR (2024)
Shujian Yu, Xi Yu, Sigurd Løkse, Robert Jenssen, José C. Príncipe
Cauchy-Schwarz Divergence Information Bottleneck for Regression. CoRR (2024)
Daniel J. Trosten, Sigurd Løkse, Robert Jenssen, Michael Kampffmeyer
Leveraging tensor kernels to reduce objective function mismatch in deep clustering. Pattern Recognit. 149 (2024)
Kristoffer K. Wickstrøm, Daniel J. Trosten, Sigurd Løkse, Ahcène Boubekki, Karl Øyvind Mikalsen, Michael C. Kampffmeyer, Robert Jenssen
RELAX: Representation Learning Explainability. Int. J. Comput. Vis. 131 (6) (2023)
Daniel J. Trosten, Sigurd Løkse, Robert Jenssen, Michael C. Kampffmeyer
On the Effects of Self-supervision and Contrastive Alignment in Deep Multi-view Clustering. CoRR (2023)
Shujian Yu, Hongming Li, Sigurd Løkse, Robert Jenssen, José C. Príncipe
The Conditional Cauchy-Schwarz Divergence with Applications to Time-Series Data and Sequential Decision Making. CoRR (2023)
Daniel J. Trosten, Sigurd Løkse, Robert Jenssen, Michael C. Kampffmeyer
On the Effects of Self-supervision and Contrastive Alignment in Deep Multi-view Clustering. CVPR (2023)
Daniel J. Trosten, Rwiddhi Chakraborty, Sigurd Løkse, Kristoffer Knutsen Wickstrøm, Robert Jenssen, Michael C. Kampffmeyer
Hubs and Hyperspheres: Reducing Hubness and Improving Transductive Few-shot Learning with Hyperspherical Embeddings. CoRR (2023)
Kristoffer K. Wickstrøm, Sigurd Løkse, Michael C. Kampffmeyer, Shujian Yu, José C. Príncipe, Robert Jenssen
Analysis of Deep Convolutional Neural Networks Using Tensor Kernels and Matrix-Based Entropy. Entropy 25 (6) (2023)
Daniel J. Trosten, Rwiddhi Chakraborty, Sigurd Løkse, Kristoffer Knutsen Wickstrøm, Robert Jenssen, Michael C. Kampffmeyer
Hubs and Hyperspheres: Reducing Hubness and Improving Transductive Few-Shot Learning with Hyperspherical Embeddings. CVPR (2023)
Kristoffer Wickstrøm, Juan Emmanuel Johnson, Sigurd Løkse, Gustau Camps-Valls, Karl Øyvind Mikalsen, Michael Kampffmeyer, Robert Jenssen
The Kernelized Taylor Diagram. CoRR (2022)
Kristoffer Wickstrøm, Juan Emmanuel Johnson, Sigurd Løkse, Gustau Camps-Valls, Karl Øyvind Mikalsen, Michael Kampffmeyer, Robert Jenssen
The Kernelized Taylor Diagram. NAIS (2022)
Daniel J. Trosten, Sigurd Løkse, Robert Jenssen, Michael Kampffmeyer
Reconsidering Representation Alignment for Multi-View Clustering. CVPR (2021)
Filippo Maria Bianchi, Simone Scardapane, Sigurd Løkse, Robert Jenssen
Reservoir Computing Approaches for Representation and Classification of Multivariate Time Series. IEEE Trans. Neural Networks Learn. Syst. 32 (5) (2021)
Daniel J. Trosten, Sigurd Løkse, Robert Jenssen, Michael Kampffmeyer
Reconsidering Representation Alignment for Multi-view Clustering. CoRR (2021)
Kristoffer K. Wickstrøm, Daniel J. Trosten, Sigurd Løkse, Karl Øyvind Mikalsen, Michael C. Kampffmeyer, Robert Jenssen
RELAX: Representation Learning Explainability. CoRR (2021)
Van Nhan Nguyen, Sigurd Løkse, Kristoffer Wickstrøm, Michael Kampffmeyer, Davide Roverso, Robert Jenssen
SEN: A Novel Feature Normalization Dissimilarity Measure for Prototypical Few-Shot Learning Networks. ECCV (23) (2020)
Michael Kampffmeyer, Sigurd Løkse, Filippo Maria Bianchi, Lorenzo Livi, Arnt-Børre Salberg, Robert Jenssen
Deep Divergence-Based Approach to Clustering. CoRR (2019)
Kristoffer Wickstrøm, Sigurd Løkse, Michael Kampffmeyer, Shujian Yu, José C. Príncipe, Robert Jenssen
Information Plane Analysis of Deep Neural Networks via Matrix-Based Renyi's Entropy and Tensor Kernels. CoRR (2019)
Michael Kampffmeyer, Sigurd Løkse, Filippo Maria Bianchi, Lorenzo Livi, Arnt-Børre Salberg, Robert Jenssen
Deep divergence-based approach to clustering. Neural Networks 113 (2019)
Michael Kampffmeyer, Sigurd Løkse, Filippo Maria Bianchi, Robert Jenssen, Lorenzo Livi
The deep kernelized autoencoder. Appl. Soft Comput. 71 (2018)
Filippo Maria Bianchi, Simone Scardapane, Sigurd Løkse, Robert Jenssen
Reservoir computing approaches for representation and classification of multivariate time series. CoRR (2018)
Michael Kampffmeyer, Sigurd Løkse, Filippo Maria Bianchi, Robert Jenssen, Lorenzo Livi
The Deep Kernelized Autoencoder. CoRR (2018)
Filippo Maria Bianchi, Simone Scardapane, Sigurd Løkse, Robert Jenssen
Bidirectional deep-readout echo state networks. ESANN (2018)
Jonas Nordhaug Myhre, Karl Øyvind Mikalsen, Sigurd Løkse, Robert Jenssen
Robust clustering using a kNN mode seeking ensemble. Pattern Recognit. 76 (2018)
Sigurd Løkse, Robert Jenssen
Ranking Using Transition Probabilities Learned from Multi-Attribute Data. ICASSP (2018)
Michael Kampffmeyer, Sigurd Løkse, Filippo Maria Bianchi, Robert Jenssen, Lorenzo Livi
Deep Kernelized Autoencoders. CoRR (2017)
Michael Kampffmeyer, Sigurd Løkse, Filippo Maria Bianchi, Robert Jenssen, Lorenzo Livi
Deep Kernelized Autoencoders. SCIA (1) (2017)
Filippo Maria Bianchi, Simone Scardapane, Sigurd Løkse, Robert Jenssen
Bidirectional deep echo state networks. CoRR (2017)
Michael Kampffmeyer, Sigurd Løkse, Filippo Maria Bianchi, Lorenzo Livi, Arnt-Børre Salberg, Robert Jenssen
Deep divergence-based clustering. MLSP (2017)
Sigurd Løkse, Filippo Maria Bianchi, Robert Jenssen
Training Echo State Networks with Regularization Through Dimensionality Reduction. Cogn. Comput. 9 (3) (2017)
Sigurd Løkse, Filippo Maria Bianchi, Arnt-Børre Salberg, Robert Jenssen
Spectral Clustering Using PCKID - A Probabilistic Cluster Kernel for Incomplete Data. SCIA (1) (2017)
Sigurd Løkse, Filippo Maria Bianchi, Robert Jenssen
Training Echo State Networks with Regularization through Dimensionality Reduction. CoRR (2016)
Jonas Nordhaug Myhre, Karl Øyvind Mikalsen, Sigurd Løkse, Robert Jenssen
Consensus Clustering Using kNN Mode Seeking. SCIA (2015)