Institutt for matematikk og statistikk: Recent submissions
Now showing items 81-100 of 412
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Simplifying Clustering with Graph Neural Networks
(Journal article; Tidsskriftartikkel; Peer reviewed, 2023-01-23)The objective functions used in spectral clustering are generally composed of two terms: i) a term that minimizes the local quadratic variation of the cluster assignments on the graph and; ii) a term that balances the clustering partition and helps avoiding degenerate solutions. This paper shows that a graph neural network, equipped with suitable message passing layers, can generate good cluster ... -
The global atmospheric energy transport analysed by a wavelength-based scale separation
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022)The global atmospheric circulation is fundamental for the local weather and climate by redistributing energy and moisture. To the present day, there is a knowledge gap at which spatial scales the energy and its components are transported. Therefore, we separate the meridional atmospheric energy transport in the ERA5 reanalysis by the spatial scales, the quasi-stationary and transient flow patterns, ... -
A global climatology of polar lows investigated for local differences and wind-shear environments
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022-04-11)Polar lows are intense mesoscale cyclones developing in marine polar air masses. This study presents a new global climatology of polar lows based on the ERA5 reanalysis for the years 1979–2020. Criteria for the detection of polar lows are derived based on a comparison of five polarlow archives with cyclones derived by a mesoscale tracking algorithm. The characteristics associated with polar lows are ... -
Hyperbolic cone metrics and billiards
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022-08-31)A negatively curved hyperbolic cone metric is called rigid if it is determined (up to isotopy) by the support of its Liouville current, and flexible otherwise. We provide a complete characterization of rigidity and flexibility, prove that rigidity is a generic property, and parameterize the associated deformation space for any flexible metric. As an application, we parameterize the space of ... -
Almost every path structure is not variational
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022-10-15)Given a smooth family of unparameterized curves such that through every point in every direction there passes exactly one curve, does there exist a Lagrangian with extremals being precisely this family? It is known that in dimension 2 the answer is positive. In dimension 3, it follows from the work of Douglas that the answer is, in general, negative. We generalise this result to all higher dimensions ... -
Lattice conditional independence models and Hibi ideals
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022-06-10)Lattice conditional independence models [Andersson and Perlman, Lattice models for conditional independence in a multivariate normal distribution, Ann. Statist. 21 (1993), 1318–1358] are a class of models developed first for the Gaussian case in which a distributive lattice classifies all the conditional independence statements. The main result is that these models can equivalently be described via ... -
Seasonality, density dependence, and spatial population synchrony
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022-12-15)Studies of spatial population synchrony constitute a central approach for understanding the drivers of ecological dynamics. Recently, identifying the ecological impacts of climate change has emerged as a new important focus in population synchrony studies. However, while it is well known that climatic seasonality and sequential density dependence influences local population dynamics, the role of ... -
Differential invariants of curves in G2 flag varieties
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022-05-10)We compute the algebra of differential invariants of unparametrized curves in the homogeneous G<sub>2</sub> flag varieties, namely in G<sub>2</sub>/P. This gives a solution to the equivalence problem for such curves. We consider the cases of integral and generic curves and relate the equivalence problems for all three choices of the parabolic subgroup P. -
Power Flow Balancing With Decentralized Graph Neural Networks
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022-08-01)We propose an end-to-end framework based on a Graph Neural Network (GNN) to balance the power flows in energy grids. The balancing is framed as a supervised vertex regression task, where the GNN is trained to predict the current and power injections at each grid branch that yield a power flow balance. By representing the power grid as a line graph with branches as vertices, we can train a GNN that ... -
Understanding Pooling in Graph Neural Networks
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022-07-21)Many recent works in the field of graph machine learning have introduced pooling operators to reduce the size of graphs. In this article, we present an operational framework to unify this vast and diverse literature by describing pooling operators as the combination of three functions: selection, reduction, and connection (SRC). We then introduce a taxonomy of pooling operators, based on some of ... -
An Energy Balance Model on an Infinite Line
(Master thesis; Mastergradsoppgave, 2022-06-01)The thesis is an expansion of the work Gerald R. North did in 1975 on an energy balance climate model. By considering a similar model on an infinite line, and allowing the heat diffusion coefficient to vary on the line, more complicated behaviour arose from the model. Much of Norths work was recreated on the infinite lines, but a lot of new discoveries were made. Among what was found were spontaneous ... -
Explainability in subgraphs-enhanced Graph Neural Networks
(Journal article; Tidsskriftartikkel, 2023)Recently, subgraphs-enhanced Graph Neural Networks (SGNNs) have been introduced to enhance the expressive power of Graph Neural Networks (GNNs), which was proved to be not higher than the 1-dimensional Weisfeiler-Leman isomorphism test. The new paradigm suggests using subgraphs extracted from the input graph to improve the model’s expressiveness, but the additional complexity exacerbates an ... -
Comprehensive uncertainty estimation of the timing of Greenland warmings in the Greenland ice core records
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022-06-20)Paleoclimate proxy records have non-negligible uncertainties that arise from both the proxy measurement and the dating processes. Knowledge of the dating uncertainties is important for a rigorous propagation to further analyses, for example, for identification and dating of stadial– interstadial transitions in Greenland ice core records during glacial intervals, for comparing the variability in ... -
Weight spectra of Gabidulin rank-metric codes and Betti numbers
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022-07-07)The Helmholtz equation has been used for modeling the sound pressure field under a harmonic load. Computing harmonic sound pressure fields by means of solving Helmholtz equation can quickly become unfeasible if one wants to study many different geometries for ranges of frequencies. We propose a machine learning approach, namely a feedforward dense neural network, for computing the average sound ... -
Kinetic energy-free Hartree–Fock equations: an integral formulation
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022-07-18)We have implemented a self-consistent feld solver for Hartree–Fock calculations, by making use of Multiwavelets and Multiresolution Analysis. We show how such a solver is inherently a preconditioned steepest descent method and therefore a good starting point for rapid convergence. A distinctive feature of our implementation is the absence of any reference to the kinetic energy operator. This is ... -
Recognition of polar lows in Sentinel-1 SAR images with deep learning
(Journal article; Tidsskriftartikkel, 2022-09-06)In this article, we explore the possibility of detecting polar lows in C-band synthetic aperture radar (SAR) images by means of deep learning. Specifically, we introduce a novel dataset consisting of Sentinel-1 images divided into two classes, representing the presence and absence of a maritime mesocyclone, respectively. The dataset is constructed using the ECMWF reanalysis version 5 (ERA5) dataset ... -
Identifying dietary patterns across age, educational level and physical activity level in a cross-sectional study: the Tromsø Study 2015 - 2016
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022-09-15)<p><b>Background</b> A healthy diet can decrease the risk of several lifestyle diseases. From studying the health effects of single foods, research now focuses on examining complete diets and dietary patterns reflecting the combined intake of different foods. The main goals of the current study were to identify dietary patterns and then investigate how these differ in terms of sex, age, educational ... -
Personalized optimization of blood glucose regulation: A Diabetes Mellitus case study
(Mastergradsoppgave; Master thesis, 2022-07-13)Type 1 diabetes (T1D) is a chronic autoimmune disease that leads to insulin deficiency. Consequently, the disease will lead to a poor blood glucose (BG) regulation, and in situations of high energy expenditure like exercise, a dysfunctional regulation can cause severe damage or death [5] [14]. Diabetes is responsible for one death every five seconds and financially drains approximately 11% of the ... -
Codes from symmetric polynomials
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022-10-10)We define and study a class of Reed–Muller type error-correcting codes obtained from elementary symmetric functions in finitely many variables. We determine the code parameters and higher weight spectra in the simplest cases. -
On structure of linear differential operators, acting on line bundles
(Journal article; Tidsskriftartikkel; Peer reviewed, 2019-11-14)We study differential invariants of linear differential operators and use them to find conditions for equivalence of differential operators acting on line bundles over smooth manifolds with respect to groups of automorphisms.