Now showing items 61-80 of 316

    • Seasonality, density dependence, and spatial population synchrony 

      Antunes Lopes Da Silva Nicolau, Pedro Guilherme; Ims, Rolf Anker; Sørbye, Sigrunn Holbek; Yoccoz, Nigel (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 

      Kruglikov, Boris; Llabrés, Andreu (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 

      Hansen, Jonas Berg; Anfinsen, Stian Normann; Bianchi, Filippo Maria (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 

      Grattarola, Daniele; Zambon, Daniele; Bianchi, Filippo Maria; Alippi, Cesare (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 ...
    • Explainability in subgraphs-enhanced Graph Neural Networks 

      Guerra, Michele; Bianchi, Filippo Maria; Scardapane, Simone; Spinelli, Indro (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 

      Myrvoll-Nilsen, Eirik; Riechers, Keno; Rypdal, Martin Wibe; Boers, Niklas (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 

      Johnsen, Trygve; Pratihar, Rakhi; Verdure, Hugues (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 

      Jensen, Stig Rune; Durdek, Antoine Pacifique Romain; Bjørgve, Magnar; Wind, Peter; Flå, Tor; Frediani, Luca (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 

      Grahn, Jakob; Bianchi, Filippo Maria (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 

      Moe, Åse Mari; Sørbye, Sigrunn Holbek; Hopstock, Laila Arnesdatter; Carlsen, Monica Hauger; Løvsletten, Ola; Ytterstad, Elinor (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 ...
    • Codes from symmetric polynomials 

      Johnsen, Trygve; Datta, Mrinmoy (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 

      Lychagin, Valentin; Yumaguzhin, Valeriy (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.
    • On Multi-Rule and Probability-Dependant Adaptations of Conway’s Game of Life and Their Character 

      Cotronei, Alessandro (Journal article; Tidsskriftartikkel; Peer reviewed, 2022)
      We introduce some novel adaptations of Life-Like Automata. We focus mainly on some modifications of the original rules where the evolution of the system is depending from the step and the zone of the grid. We study also the properties of some novel non-deterministic adaptations.
    • Symmetry gaps for higher order ordinary differential equations 

      Kessy, Johnson Allen; The, Dennis (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-07-04)
      The maximal contact symmetry dimensions for scalar ODEs of order ≥ 4 and vector ODEs of order ≥ 3 are well known. Using a Cartan-geometric approach, we determine for these ODEs the next largest realizable (submaximal) symmetry dimension. Moreover, finer curvature-constrained submaximal symmetry dimensions are also classified.
    • Data-Driven Robust Control Using Reinforcement Learning 

      Ngo, Phuong; Tejedor Hernandez, Miguel Angel; Godtliebsen, Fred (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-02-21)
      This paper proposes a robust control design method using reinforcement learning for controlling partially-unknown dynamical systems under uncertain conditions. The method extends the optimal reinforcement learning algorithm with a new learning technique based on the robust control theory. By learning from the data, the algorithm proposes actions that guarantee the stability of the closed-loop system ...
    • Symmetries of supergeometries related to nonholonomic superdistributions 

      Kruglikov, Boris; Santi, Andrea; The, Dennis (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-06-06)
      We extend Tanaka theory to the context of supergeometry and obtain an upper bound on the supersymmetry dimension of geometric structures related to strongly regular bracket-generating distributions on supermanifolds and their structure reductions.
    • Greedy weights for matroids 

      Johnsen, Trygve; Verdure, Hugues (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-12-19)
      We introduce greedy weights of matroids, inspired by those for linear codes. We show that a Wei duality holds for two of these types of greedy weights for matroids. Moreover we show that in the cases where the matroids involved are associated to linear codes, our definitions coincide with those for codes. Thus our Wei duality is a generalization of that for linear codes given by Schaathun. In ...
    • Overview of the MOSAiC expedition: Physical oceanography 

      Rabe, Benjamin; Baumann, Till Martin; Divine, Dmitry; Fer, Ilker; Gradinger, Rolf Rudolf; Granskog, Mats; Koenig, Zoe Charlotte; Muilwijk, Morven; Sundfjord, Arild; Heuze´, Céline; Regnery, Julia; Aksenov, Yevgeny; Allerholt, Jacob; Athanase, Marylou; Bai, Youcheng; Basque, Chris; Bauch, Dorothea; Chen, Dake; Cole, Sylvia T.; Craw, Lisa; Davies, Andrew; Damm, Ellen; Dethloff, Klaus; Doglioni, Francesca; Ebert, Falk; Fang, Ying-Chih; Fong, Allison A.; Graupner, Rainer; Haas, Christian; He, Hailun; He, Yan; Hoppmann, Mario; Janout, Markus; Kadko, David; Kanzow, Torsten; Karam, Salar; Kawaguchi, Yusuke; Kong, Bin; Krishfield, Richard A.; Krumpen, Thomas; Kuhlmey, David; Kuznetsov, Ivan; Lan, Musheng; Laukert, Georgi; Lei, Ruibo; Li, Lao; Torres-Valdés, Sinhué; Lin, Lina; Lin, Long; Liu, Hailong; Liu, Na; Loose, Brice; Ma, Xiaobing; McKay, Rosalie; Mallet, Maria; Mallet, Robbie D .C.; Maslowski, Wieslaw; Mertens, Christian; Mohrholz, Volker; Nicolaus, Marcel; O'Brien, Jeffrey K.; Perovich, Donald; Ren, Jian; Rex, Markus; Ribeiro, Natalia; Rinke, Annette; Sokolov, Vladimir; Sommerfeld, Anja; Spreen, Gunnar; Stanton, Timothy; Stephens, Mark; Su, Jie; Sukhikh, Natalia; Thomisch, Karolin; Tippenhauer, Sandra; Toole, John M.; Vredenborg, Myriel; Walter, Maren; Wang, Hangzhou; Wang, Lei; Wang, Yuntao; Wendisch, Manfred; Zhao, Jinping; Zhou, Meng; Zhu, Jialiang (Journal article; Tidsskriftartikkel; Peer reviewed, 2022-02-07)
      Arctic Ocean properties and processes are highly relevant to the regional and global coupled climate system, yet still scarcely observed, especially in winter. Team OCEAN conducted a full year of physical oceanography observations as part of the Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC), a drift with the Arctic sea ice from October 2019 to September 2020. ...
    • 25 years of self-organized criticality: concepts and controversies 

      Watkins, Nicholas W.; Pruessner, Gunnar; Chapman, Sandra; Crosby, Norma B; Jensen, Henrik J (Journal article; Tidsskriftartikkel; Peer reviewed, 2015-05-28)
      Introduced by the late Per Bak and his colleagues, self-organized criticality (SOC) has been one of the most stimulating concepts to come out of statistical mechanics and condensed matter theory in the last few decades, and has played a significant role in the development of complexity science. SOC, and more generally fractals and power laws, have attracted much comment, ranging from the very ...
    • Classification of simply-transitive Levi non-degenerate hypersurfaces in C^3 

      Doubrov, Boris; Merker, Joël; The, Dennis (Journal article; Tidsskriftartikkel; Peer reviewed, 2021-06-24)
      Holomorphically homogeneous Cauchy–Riemann (CR) real hypersurfaces <i>M<i/><sup>3</sup>⊂C<sup>2</sup> were classified by Élie Cartan in 1932. In the next dimension, we complete the classification of simply-transitive Levi non-degenerate hypersurfaces <i>M<i/><sup>5</sup>⊂C<sup>3</sup> using a novel Lie algebraic approach independent of any earlier classifications of abstract Lie algebras. Central ...