Daniel J. Trosten

Int. J. Comput. Vis., June, 2023

Questionable Practices in Methodological Deep Learning Research.

[BibT_eX]

[DOI]

Proceedings of the 2023 Northern Lights Deep Learning Workshop, 2023

On the Effects of Self-supervision and Contrastive Alignment in Deep Multi-view Clustering.

[BibT_eX]

[DOI]

Sigurd Løkse

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Hubs and Hyperspheres: Reducing Hubness and Improving Transductive Few-Shot Learning with Hyperspherical Embeddings.

[BibT_eX]

[DOI]

Kristoffer Knutsen Wickstrøm

Rwiddhi Chakraborty

Sigurd Løkse

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2021

RELAX: Representation Learning Explainability.

[BibT_eX]

[DOI]

Kristoffer K. Wickstrøm

Sigurd Løkse

Karl Øyvind Mikalsen

CoRR, 2021

Reducing Objective Function Mismatch in Deep Clustering with the Unsupervised Companion Objective.

[BibT_eX]

[DOI]

Proceedings of the 2021 Northern Lights Deep Learning Workshop, 2021

Reconsidering Representation Alignment for Multi-View Clustering.

[BibT_eX]

[DOI]

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

2020

Deep Image Clustering with Tensor Kernels and Unsupervised Companion Objectives.

[BibT_eX]

[DOI]

CoRR, 2020

2019

Unsupervised Feature Extraction - A CNN-Based Approach.

[BibT_eX]

[DOI]

Puneet Sharma

Proceedings of the Image Analysis - 21st Scandinavian Conference, 2019

Recurrent Deep Divergence-based Clustering for Simultaneous Feature Learning and Clustering of Variable Length Time Series.

[BibT_eX]

[DOI]

Andreas Storvik Strauman

Michael Kampffmeyer