Scientific publications

At Visual Intelligence we work across our innovation areas to extract knowledge from large volumes of visual data more efficiently through automatic and intelligent data analysis. The work to address the core research challenges in deep learning: working with limited training data, utilizing context and dependencies, providing explainability, confidence and uncertainty, are important in all the innovation areas.

Featured blog posts

Interrogating Sea Ice Predictability With Gradients

February 14, 2024
By
Joakimsen, H. L., Martinsen I., Luppino, L. T., McDonald, A., Hosking, S., and Jenssen, R.

Merging clustering into deep supervised neural network

June 4, 2023
By
Durgesh Singh, Ahcéne Boubekki, Robert Jenssen, Michael C. Kampffmeyer

All publications

The Meta-Evaluation Problem in Explainable AI: Identifying Reliable Estimators with MetaQuantus

By authors:

Anna Hedström, Philine Lou Bommer, Kristoffer Knutsen Wickstrøm, Wojciech Samek, Sebastian Lapuschkin, Marina MC Höhne

Published in:

Transactions on Machine Learning Research (06/2023)

on

June 1, 2023

Learning Fair Representations through Uniformly Distributed Sensitive Attributes

By authors:

Kenfack, Patrik; Ramírez Rivera, Adín; Khan, Adil; Mazzara, Manuel

Published in:

2023 IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), Raleigh, NC, USA, 2023, pp. 58-67

on

June 1, 2023

Explaining Image Classifiers with Multiscale Directional Image Representation

By authors:

Stefan Kolek, Robert Windesheim, Hector Andrade-Loarca, Gitta Kutyniok, Ron Levie

Published in:

2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Vancouver, BC, Canada, 2023 pp. 18600-18609.

on

June 1, 2023

A clinically motivated self-supervised approach for content-based image retrieval of CT liver images

By authors:

Wickstrøm, Kristoffer; Østmo, Eirik Agnalt; Radiya, Keyur; Mikalsen, Karl Øyvind; Kampffmeyer, Michael; Jenssen, Robert.

Published in:

Computerized Medical Imaging and Graphics 2023 ;Volum 107. s.1-12

on

May 9, 2023

Distributed extra-gradient with optimal complexity and communication guarantees

By authors:

Ali Ramezani-Kebrya, Kimon Antonakopoulos, Igor Krawczuk, Justin Deschenaux, Volkan Cevher

Published in:

International Conference on Learning Representations ICLR 2023

on

May 1, 2023

Self-supervised Learning of Contextualized Local Visual Embeddings.

By authors:

Silva, Thalles; Pedrini, Helio; Ramírez Rivera, Adín.

Published in:

2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW). IEEE (Institute of Electrical and Electronics Engineers) 2023

on

May 1, 2023

Automatic Identification of Chemical Moieties

By authors:

Jonas Lederer, Michael Gastegger, Kristof T. Schütt, Michael Kampffmeyer, Klaus-Robert Müller, and Oliver T. Unke

Published in:

Physical Chemistry Chemical Physics 2023

on

April 27, 2023

Predicting Regions of Local Recurrence in Glioblastomas Using Voxel-Based Radiomic Features of Multiparametric Postoperative MRI

By authors:

Cepeda, Santiago and Luppino, Luigi Tommaso and Pérez-Núñez, Angel and Solheim, Ole and García-García, Sergio and Velasco-Casares, María and Karlberg, Anna and Eikenes, Live and Sarabia, Rosario and Arrese, Ignacio and Zamora, Tomás and Gonzalez, Pedro and Jiménez-Roldán, Luis and Kuttner, Samuel

Published in:

Cancers. 2023; 15(6):1894.

on

March 22, 2023

RELAX: Representation Learning Explainability

By authors:

Wickstrøm, Kristoffer; Trosten, Daniel Johansen; Løkse, Sigurd Eivindson; Boubekki, Ahcene; Mikalsen, Karl Øyvind; Kampffmeyer, Michael; Jenssen, Robert

Published in:

International Journal of Computer Vision 2023 ;Volum 131.(6) s.1584-1610

on

March 11, 2023

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

By authors:

Daniel J. Trosten, Sigurd Løkse, Robert Jenssen, Michael Kampffmeyer.

Published in:

Computer Vision and Pattern Recognition 2023 s.23976-23985

on

March 6, 2023

Other publications

annual reports