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S. Mitusch, S. W. Funke and M. Kuchta

Hybrid FEM-NN models: Combining artificial neural networks with the finite element method

Journal of Computational Physics (2021).
Journal Article
2021
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L. M. Valnes, S. Mitusch, G. Ringstad, P. K. Eide, S. W. Funke and K. Mardal

Apparent diffusion coefficient estimates based on 24 hours tracer movement support glymphatic transport in human cerebral cortex

Scientific Reports 10, no. 1 (2020).
Journal Article
2020
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S. Mitusch, S. W. Funke and J. S. Dokken

dolfin-adjoint 2018.1: automated adjoints for FEniCS and Firedrake

Journal of Open Source Software 4, no. 38 (2019): 1292.
Journal Article
2019
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2021

Journal articles

S. Mitusch, S. W. Funke and M. Kuchta

Hybrid FEM-NN models: Combining artificial neural networks with the finite element method

Journal of Computational Physics (2021).
Status: Submitted
2020

Journal articles

L. M. Valnes, S. Mitusch, G. Ringstad, P. K. Eide, S. W. Funke and K. Mardal

Apparent diffusion coefficient estimates based on 24 hours tracer movement support glymphatic transport in human cerebral cortex

Scientific Reports 10, no. 1 (2020).
Status: Published
2019

Journal articles

S. Mitusch, S. W. Funke and J. S. Dokken

dolfin-adjoint 2018.1: automated adjoints for FEniCS and Firedrake

Journal of Open Source Software 4, no. 38 (2019): 1292.
Status: Published

Posters

S. Mitusch and S. W. Funke

Algorithmic differentiation for coupled FEniCS and PyTorch models

ICCOPT, Berlin, Germany, 2019.
Status: Published
2017

Posters

S. Mitusch and S. W. Funke

A new algorithmic differentiation tool (not only) for FEniCS

FEniCS 2017 conference, Luxembourg, 2017.
Status: Published