Viser treff 141-160 av 389

    • Hierarchical Representation Learning in Graph Neural Networks with Node Decimation Pooling 

      Bianchi, Filippo Maria; Grattarola, Daniele; Livi, Lorenzo; Alippi, Cesare (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-12-31)
      In graph neural networks (GNNs), pooling operators compute local summaries of input graphs to capture their global properties, and they are fundamental for building deep GNNs that learn hierarchical representations. In this work, we propose the Node Decimation Pooling (NDP), a pooling operator for GNNs that generates coarser graphs while preserving the overall graph topology. During training, the ...
    • A polymatroid approach to generalized weights of rank metric codes 

      Ghorpade, Sudhir R; Johnsen, Trygve (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-09-15)
      We consider the notion of a (<i>q,m)</i>-polymatroid, due to Shiromoto, and the more general notion of (<i>q,m</i>)-demi-polymatroids, and show how generalized weights can be defined for them. Further, we establish a duality for these weights analogous to Wei duality for generalized Hamming weights of linear codes. The corresponding results of Ravagnani for Delsarte rank metric codes, and Martínez-Peñas ...
    • Relative generalized Hamming weights of affine Cartesian codes 

      Datta, Mrinmoy (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-03-10)
      We explicitly determine all the relative generalized Hamming weights of affine Cartesian codes using the notion of footprints and results from extremal combinatorics. This generalizes the previous works on the determination of relative generalized Hamming weights of Reed–Muller codes by Geil and Martin, as well as the determination of all the generalized Hamming weights of the affine Cartesian codes ...
    • Integrability via Geometry: Dispersionless Differential Equations in Three and Four Dimensions 

      Calderbank, David M. J.; Kruglikov, Boris (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-11-25)
      We prove that the existence of a dispersionless Lax pair with spectral parameter for a nondegenerate hyperbolic second order partial differential equation (PDE) is equivalent to the canonical conformal structure defined by the symbol being Einstein–Weyl on any solution in 3D, and self-dual on any solution in 4D. The first main ingredient in the proof is a characteristic property for dispersionless ...
    • Homogeneous Levi non-degenerate hypersurfaces in C3 

      Doubrov, Boris; Medvedev, Alexandr; The, Dennis (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-06-09)
      We classify all (locally) homogeneous Levi non-degenerate real hypersurfaces in C<sup>3</sup> with symmetry algebra of dimension ≥6.
    • Blow-ups and infinitesimal automorphisms of CR-manifolds 

      Kruglikov, Boris (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-03-07)
      For a real-analytic connected CR-hypersurface M of CR-dimension n⩾1 having a point of Levi-nondegeneracy the following alternative is demonstrated for its symmetry algebra s=s(M): (i) either dims=n2+4n+3 and M is spherical everywhere; (ii) or dims⩽n2+2n+2+δ2,n and in the case of equality M is spherical and has fixed signature of the Levi form in the complement to its Levi-degeneracy locus. A version ...
    • Incorporating capture heterogeneity in the estimation of autoregressive coefficients of animal population dynamics using capture–recapture data 

      Nicolau, Pedro Guilherme; Sørbye, Sigrunn Holbek; Yoccoz, Nigel (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-08-31)
      Population dynamic models combine density dependence and environmental effects. Ignoring sampling uncertainty might lead to biased estimation of the strength of density dependence. This is typically addressed using state‐space model approaches, which integrate sampling error and population process estimates. Such models seldom include an explicit link between the sampling procedures and the true ...
    • Risk-Averse Food Recommendation Using Bayesian Feedforward Neural Networks for Patients with Type 1 Diabetes Doing Physical Activities 

      Ngo, Phuong; Tejedor Hernandez, Miguel Angel; Tayefi, Maryam; Chomutare, Taridzo; Godtliebsen, Fred (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-11-12)
      <p><i>Background.</i> Since physical activity has a high impact on patients with type 1 diabetes and the risk of hypoglycemia (low blood glucose levels) is significantly higher during and after physical activities, an automatic method to provide a personalized recommendation is needed to improve the blood glucose management and harness the benefits of physical activities. This paper aims to reduce ...
    • Generalized eigenvalue methods for Gaussian quadrature rules 

      Blekherman, Grigoriy; Kummer, Mario; Riener, Cordian; Schweighofer, Markus; Vinzant, Cynthia (Journal article; Tidsskriftartikkel; Peer reviewed, 2020)
      A quadrature rule of a measure <i>µ</i> on the real line represents a conic combination of finitely many evaluations at points, called nodes, that agrees with integration against <i>µ</i> for all polynomials up to some fixed degree. In this paper, we present a bivariate polynomial whose roots parametrize the nodes of minimal quadrature rules for measures on the real line. We give two symmetric ...
    • A Step Towards Deep Learning-based CADs for Cancer Analysis in Medical Imaging 

      Pedersen, André (Master thesis; Mastergradsoppgave, 2019-06-01)
      In 2018, cancer was the second leading cause of death worldwide. Early detection can reduce mortality. Screening programs intended for early detection increases the workload for clinicians. To improve efficiency CAD systems would be highly beneficial. We have developed CAD systems using deep learning, for automatic tissue segmentation and prediction of diagnosis in lung and breast cancer. The ...
    • Condition Monitoring System for Internal Blowout Prevention (IBOP) in Top Drive Assembly System using Discrete Event Systems and Deep Learning Approaches 

      Noori, Nadia Saad; Waag, Tor Inge; Bianchi, Filippo Maria (Conference object; Konferansebidrag, 2020-07-19)
      <p>Offshore oil drilling is a complex process that requires careful coordination of hardware and control systems. Fault monitoring systems play an important role in such systems for safe and profitable operations. Thus, predictive maintenance and monitoring operating conditions of drilling systems are critical to the overall production cycle. In this paper, we are addressing the topic of condition ...
    • Statistical estimation of global surface temperature response to forcing under the assumption of temporal scaling 

      Myrvoll-Nilsen, Eirik; Sørbye, Sigrunn Holbek; Fredriksen, Hege-Beate; Rue, Håvard; Rypdal, Martin Wibe (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-04-08)
      Reliable quantification of the global mean surface temperature (GMST) response to radiative forcing is essential for assessing the risk of dangerous anthropogenic climate change. We present the statistical foundations for an observation-based approach using a stochastic linear response model that is consistent with the long-range temporal dependence observed in global temperature variability. We ...
    • Spectral clustering with graph neural networks for graph pooling 

      Bianchi, Filippo Maria; Grattarola, Daniele; Alippi, Cesare (Conference object; Konferansebidrag, 2020)
      Spectral clustering (SC) is a popular clustering technique to find strongly connected communities on a graph. SC can be used in Graph Neural Networks (GNNs) to implement pooling operations that aggregate nodes belonging to the same cluster. However, the eigendecomposition of the Laplacian is expensive and, since clustering results are graph-specific, pooling methods based on SC must perform a ...
    • Reservoir computing approaches for representation and classification of multivariate time series 

      Bianchi, Filippo Maria; Scardapane, Simone; Løkse, Sigurd; Jenssen, Robert (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-06-29)
      Classification of multivariate time series (MTS) has been tackled with a large variety of methodologies and applied to a wide range of scenarios. Reservoir computing (RC) provides efficient tools to generate a vectorial, fixed-size representation of the MTS that can be further processed by standard classifiers. Despite their unrivaled training speed, MTS classifiers based on a standard RC ...
    • A boundary integral approach to the modeling of surface waves in a wave tank 

      Thygesen, Sander Bøe (Master thesis; Mastergradsoppgave, 2020-06-14)
      Boundary integral equations (BIEs) are used to model surface waves in a wave tank. Assuming an ideal fluid, the velocity of the fluid can be considered as a potential flow and be modeled by the Laplace equation on the domain. The domain in this case will be a section of a wave channel with an incoming wave from the right, a rigid bottom, a reflective wall on the right and a time varying surface that ...
    • A bidirectional pulse propagation model for extreme nonlinear optics: derivation and implementation. 

      Korzeniowska, Magdalena (Master thesis; Mastergradsoppgave, 2020-05-13)
      With growing capabilities of high-intensity laser beams to generate ultra-short pulses of light, the simulation of pulse propagation in nonlinear media is expected to catch up with the front-line experimental setups. Among the challenges of nonlinear material response modeling is the ability to capture the back-scatter effect - a phenomenon inherently elusive for the well-established methods of ...
    • Validation of prediction models of severe disease course and non-achievement of remission in juvenile idiopathic arthritis part 2: Results of the Nordic model in the Canadian cohort 

      Henrey, Andrew; Rypdal, Veronika Gjertsen; Rypdal, Martin Wibe; Loughin, Thomas; Nordal, Ellen Berit; Guzman, Jaime (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-01-15)
      <b>Background</b> Validated clinical prediction models to identify children with poor prognosis at the time of juvenile idiopathic arthritis (JIA) diagnosis would be very helpful for tailoring treatments, and avoiding under- or over-treatment. Our objective was to externally validate Nordic clinical prediction models in Canadian patients with JIA. <b>Methods</b> We used data from 513 subjects ...
    • Joint Invariants of Symplectic and Contact Lie Algebra Actions 

      Andreassen, Fredrik (Master thesis; Mastergradsoppgave, 2020-06-23)
      By restricting generating functions of infinitesimal symmetries of symplectic and contact vector spaces to quadratic forms, we obtain a finite-dimensional Lie subalgebra, consisting of vector fields isomorphic to the linear symplectic or conformal symplectic algebra. This allows us to look for joint invariants of the diagonal action of g on product manifolds. We find an explicit recipe for creating ...
    • Differential Invariants of Symplectic and Contact Lie Algebra Actions 

      Jensen, Jørn Olav (Master thesis; Mastergradsoppgave, 2020-06-23)
      In this thesis we consider the equivalence problem for symplectic and conformal symplectic group actions on submanifolds and functions. We solve the equivalence problem for general submanifolds by means of computing differential invariants and describing all the invariants of the associated group action by appealing to the Lie-Tresse theorem.
    • Homogeneous Levi non-degenerate hypersurfaces in C^3 

      Doubrov, Boris; Medvedev, Alexandr; The, Dennis (Journal article; Tidsskriftartikkel; Peer reviewed, 2020-06-09)
      We classify all (locally) homogeneous Levi non-degenerate real hypersurfaces in C<sup>3</sup> with symmetry algebra of dimension ≥6.