Browsing NTNU Open by Author "Celledoni, Elena"

Now showing items 21-40 of 60

    • Explicit, A Priori Constrained Model Parameterization for Inverse Problems, Applied on Geophysical CSEM Data 

      Skrede, Ole-Johan (Master thesis, 2014)
      This thesis introduce a new parameterization of the model space in global inversion problems. The parameterization provides an explicit representation of the model space with a basis constrained on a priori information ...

    • Geometric and integrability properties of Kahan?s method: The preservation of certain quadratic integrals 

      Celledoni, Elena; McLaren, David; Owren, Brynjulf; Quispel, Reinout (Peer reviewed; Journal article, 2019)
      Given a quadratic vector field on possessing a quadratic first integral depending on two of the independent variables, we give a constructive proof that Kahan's discretization method exactly preserves a nearby modified ...

    • Gradient-Based Optimization in Shape Analysis for Reparametrization of Parametric Curves and Surfaces 

      Riseth, Jørgen Nilsen (Master thesis, 2021)
      I denne oppgaven studerer vi to gradientbaserte optimeringsalgoritmer i formanalyse, for reparametrisering av parametriske kurver og overflater. Den ene algoritmen er en tidligere kjent “gradient descent”-algoritme på ...

    • Group Equivariant Convolutional Neural Networks 

      Rød, Marcel Heshmati (Bachelor thesis, 2020)
      Å oppdage og klassifisere gjenstander i et bilde er en viktig underoppgave i bygge algoritmer som samhandler med den virkelige verden. I moderne applikasjoner, blir denne oppgaven løst ved hjelp av dyp læring med konvolverede. ...

    • An integral model based on slender body theory, with applications to curved rigid fibers 

      Andersson, Helge Ingolf; Celledoni, Elena; Ohm, Laurel; Owren, Brynjulf; Tapley, Benjamin (Peer reviewed; Journal article, 2021)
      We propose a novel integral model describing the motion of both flexible and rigid slender fibers in viscous flow and develop a numerical method for simulating dynamics of curved rigid fibers. The model is derived from ...

    • Inverse Dynamics of Mechanical Multibody Systems with Servo Constraints and Geometrically Exact Strings 

      Strøm, Gard Christoffer (Master thesis, 2024)
      Denne masteroppgaven har som mål å fullføre numeriske beregninger av det inverse dynamikkproblemet for mekaniske multilegemesystemer og for geometrisk eksakte strenger for å validere eksisterende teori og beregne analytiske ...

    • Krylov projection methods for linear Hamiltonian systems 

      Li, Lu; Celledoni, Elena (Journal article; Peer reviewed, 2019)
      We study geometric properties of Krylov projection methods for large and sparse linear Hamiltonian systems. We consider in particular energy-preservation. We discuss the connection to structure preserving model reduction. ...

    • Krylovmetoder for lineære hamiltonske differensiallikninger 

      Eskeland, Sindre (Master thesis, 2016)
      Krylovmetoder er projeksjonsmetoder som kan transformere store lineære differensialligninger til mindre lineære differesialligninger med lignende egenskaper. To slike metoder (symplectic Lanczos method og Krylov projection ...

    • Learning dynamical systems from noisy data with inverse-explicit integrators 

      Celledoni, Elena; Eidnes, Sølve; Myhr, Håkon Noren (Peer reviewed; Journal article, 2024)
      We introduce the mean inverse integrator (MII), a novel approach that improves accuracy when training neural networks to approximate vector fields of dynamical systems using noisy data. This method can be used to average ...

    • Learning Hamiltonians of constrained mechanical systems 

      Celledoni, Elena; Leone, Andrea; Murari, Davide; Owren, Brynjulf (Peer reviewed; Journal article, 2022)
      Recently, there has been an increasing interest in modelling and computation of physical systems with neural networks. Hamiltonian systems are an elegant and compact formalism in classical mechanics, where the dynamics is ...

    • Lie Group integrators for mechanical systems 

      Celledoni, Elena; Çokaj, Ergys; Leone, Andrea; Murari, Davide; Owren, Brynjulf (Peer reviewed; Journal article, 2021)
      Since they were introduced in the 1990s, Lie group integrators have become a method of choice in many application areas. These include multibody dynamics, shape analysis, data science, image registration and biophysical ...

    • Neural networks for the approximation of Euler’s elastica 

      Celledoni, Elena; Çokaj, Ergys; Leone, Andrea; Leyendecker, Sigrid; Murari, Davide; Owren, Brynjulf Rustad; Sato Martín de Almagro, Rodrigo T; Stavole, Martina (Journal article; Peer reviewed, 2025)
      Euler’s elastica is a classical model of flexible slender structures relevant in many industrial applications. Static equilibrium equations can be derived via a variational principle. The accurate approximation of solutions ...

    • Neural Networks on Low-Rank and Stiefel Manifolds 

      Klemetsen, Camilla Balestrand (Master thesis, 2022)
      I denne oppgaven ser vi på effekten av dyp læring som optimal kontroll på mangfoldigheter. Vi utvikler og trener flere nettverk som bevarer lav-rang og ortogonalitet i treningsprosessen. Bibetingelsen til optimal kontroll ...

    • Neural Networks, Differential Equations, and Structure Preservation 

      Murari, Davide (Doctoral theses at NTNU;2024:364, Doctoral thesis, 2024)

    • Noise removal in synthetically generated diffusion tensor imaging data using a denoising autoencoder 

      Wiik, Anders (Bachelor thesis, 2020)
      Diffusjonstensor avbildning (DTI) er en populær medisinsk avbildningsteknikk som kartlegger diffusjonen av vannmolekyler i biologisk vev. Målte DTI-data er forurenset av støy, og temaet for dette prosjektet var å utforske ...

    • A novel approach to rigid spheroid models in viscous flows using operator splitting methods 

      Tapley, Benjamin; Celledoni, Elena; Owren, Brynjulf; Andersson, Helge Ingolf (Peer reviewed; Journal article, 2019)
      Calculating cost-effective solutions to particle dynamics in viscous flows is an important problem in many areas of industry and nature. We implement a second-order symmetric splitting method on the governing equations for ...

    • Numerical integration in inverse problems for ordinary differential equations 

      Noren, Håkon (Master thesis, 2022)
      Dersom ein kjenner punkter av løysinga til ei ordinær differensiallikning (ODE), handlar det inverse problemet om å finne ein approksimasjon av vektorfeltet. Ei forskingsretning som nyleg har vorte særs aktiv, dreier seg ...

    • Numerical Methods for Nonholonomic Mechanics 

      Hilden, Sindre Kristensen (Master thesis, 2009)
      We discuss nonholonomic systems in general and numerical methods for solving them. Two different approaches for obtaining numerical methods are considered; discretization of the Lagrange-d'Alembert equations on the one ...

    • Numerical Methods for Nonholonomic Rigid Body Dynamics 

      Høiseth, Eirik Hoel (Master thesis, 2011)
      We discuss general nonholonomic systems on manifolds in the setting of both continousand discrete mechanics, before focusing on systems with symmetry that enable a reduction of the equations of motion to a quotient space ...

    • Numerical Simulation of Nonholonomic Dynamics 

      Evensberget, Dag Frohde (Master thesis, 2006)
      We study the numerical integration of nonholonomic problems. The problems are formulated using Lagrangian and Hamiltonian mechanics. We review briefly the theoretical concepts used in geometric mechanics. We reconstruct ...