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  1. Employees

Språkvelger

Norsk

Håkon Noren Myhr

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Håkon Noren Myhr

PhD Candidate
Department of Mathematical Sciences

hakon.noren@ntnu.no
Realfagbygget, Gløshaugen
Publications Teaching Outreach

Publications

  • Chronological
  • By category
  • See all publications in Cristin

2024

  • Myhr, Håkon Noren; Eidnes, Sølve. (2024) Derivative-free discrete gradient methods. Journal of Computational Dynamics
    Academic article
  • Celledoni, Elena; Eidnes, Sølve; Myhr, Håkon Noren. (2024) Learning dynamical systems from noisy data with inverse-explicit integrators. Physica D : Non-linear phenomena
    Academic article

2023

  • Myhr, Håkon Noren. (2023) Learning Hamiltonian Systems with Mono-Implicit Runge-Kutta Methods. Lecture Notes in Computer Science (LNCS)
    Academic article
  • Myhr, Håkon Noren. (2023) Mapping lakes and learning Hamiltonians. ECMI Newsletter
    Popular scientific article

Journal publications

  • Myhr, Håkon Noren; Eidnes, Sølve. (2024) Derivative-free discrete gradient methods. Journal of Computational Dynamics
    Academic article
  • Celledoni, Elena; Eidnes, Sølve; Myhr, Håkon Noren. (2024) Learning dynamical systems from noisy data with inverse-explicit integrators. Physica D : Non-linear phenomena
    Academic article
  • Myhr, Håkon Noren. (2023) Learning Hamiltonian Systems with Mono-Implicit Runge-Kutta Methods. Lecture Notes in Computer Science (LNCS)
    Academic article
  • Myhr, Håkon Noren. (2023) Mapping lakes and learning Hamiltonians. ECMI Newsletter
    Popular scientific article

Teaching

Courses

  • TMA4205 - Numerical Linear Algebra

Outreach

2023

  • Academic lecture
    Eidnes, Sølve; Bøhn, Eivind Eigil; Lye, Kjetil Olsen; Myhr, Håkon Noren; Riemer-Sørensen, Signe; Stasik, Alexander Johannes. (2023) Pseudo-Hamiltonian neural networks. The European Consortium for Mathematics in Industry (ECMI) 22nd ECMI Conference on Industrial and Applied Mathematics , Wroclaw, Polen 2023-06-26 - 2023-06-30

2022

  • Poster
    Noren, Håkon; Celledoni, Elena; Eidnes, Sølve. (2022) Numerical integrators for learning dynamical systems from noisy data. NeurIPS The Symbiosis of Deep Learning and Differential Equations , Virtual Workshop 2022-12-09 - 2022-12-09

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