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

Visual Data Diagnosis and Debiasing with Concept Graphs

September 26, 2024
By
Chakraborty, Rwiddhi; Wang, Yinong; Gao, Jialu; Zheng, Runkai; Zhang, Cheng; De la Torre, Fernando

Modular Superpixel Tokenization in Vision Transformers

August 28, 2024
By
Marius Aasan, Odd Kolbjørnsen, Anne Schistad Solberg, Adín Ramirez Rivera

All publications

SuperCM: Revisiting Clustering for Semi-Supervised Learning

By authors:

Durgesh Singh, Ahcéne Boubekki, Robert Jenssen, Michael C. Kampffmeyer

Published in:

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

on

June 4, 2023

THE FIRST PATHLOSS RADIO MAP PREDICTION CHALLENGE

By authors:

Cagkan Yapar , Fabian Jaensch, Ron Levie‡ Gitta Kutyniok, Giuseppe Caire

Published in:

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |

on

June 4, 2023

Analysis of Deep Convolutional Neural Networks Using Tensor Kernels and Matrix-Based Entropy

By authors:

Wickstrøm, Kristoffer; Løkse, Sigurd Eivindson; Kampffmeyer, Michael; Yu, Shujian; Príncipe, José C.; Jenssen, Robert.

Published in:

Entropy 2023 ;Volum 25.(6) s.1-21

on

June 3, 2023

Federated Learning under Covariate Shifts with Generalization Guarantees

By authors:

Ali Ramezani-Kebrya, Fanghui Liu, Thomas Pethick, Grigorios Chrysos, Volkan Cevher

Published in:

Transactions on Machine Learning Research

on

June 1, 2023

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

Other publications

annual reports