108 citations · 136 across the 4 of their papers we have counts for
6 papers
The Kernelized Taylor Diagram
Kristoffer Wickstrøm, J. Emmanuel Johnson, Sigurd Løkse +4
This paper presents the kernelized Taylor diagram, a graphical framework for visualizing similarities between data populations. The kernelized Taylor diagram builds on the widely u…
Mixing Up Contrastive Learning: Self-Supervised Representation Learning for Time Series
Kristoffer Wickstrøm, Michael Kampffmeyer, Karl Øyvind Mikalsen +1
The lack of labeled data is a key challenge for learning useful representation from time series data. However, an unsupervised representation framework that is capable of producing…
Uncertainty-Aware Deep Ensembles for Reliable and Explainable Predictions of Clinical Time Series
Kristoffer Wickstrøm, Karl Øyvind Mikalsen, Michael Kampffmeyer +2
Deep learning-based support systems have demonstrated encouraging results in numerous clinical applications involving the processing of time series data. While such systems often a…
Information Plane Analysis of Deep Neural Networks via Matrix-Based Renyi's Entropy and Tensor Kernels
Kristoffer Wickstrøm, Sigurd Løkse, Michael Kampffmeyer +3
Analyzing deep neural networks (DNNs) via information plane (IP) theory has gained tremendous attention recently as a tool to gain insight into, among others, their generalization…
Uncertainty and Interpretability in Convolutional Neural Networks for Semantic Segmentation of Colorectal Polyps
Kristoffer Wickstrøm, Michael Kampffmeyer, Robert Jenssen
Convolutional Neural Networks (CNNs) are propelling advances in a range of different computer vision tasks such as object detection and object segmentation. Their success has motiv…
Understanding Convolutional Neural Networks with Information Theory: An Initial Exploration
Shujian Yu, Kristoffer Wickstrøm, Robert Jenssen +1
The matrix-based Renyi's α-entropy functional and its multivariate extension were recently developed in terms of the normalized eigenspectrum of a Hermitian matrix of the projected…