256 citations · 550 across the 15 of their papers we have counts for
19 papers
A scalable solver for a stochastic, hybrid cellular automaton model of personalized breast cancer therapy
Xiaoran Lai, Håkon A. Taskén, Torgeir Mo +4
Mathematical modeling and simulation is a promising approach to personalized cancer medicine. Yet, the complexity, heterogeneity and multi-scale nature of cancer pose significant c…
Hybrid FEM-NN models: Combining artificial neural networks with the finite element method
Sebastian K. Mitusch, Simon W. Funke, Miroslav Kuchta
We present a methodology combining neural networks with physical principle constraints in the form of partial differential equations (PDEs). The approach allows to train neural net…
Automatic shape derivatives for transient PDEs in FEniCS and Firedrake
Jørgen S. Dokken, Sebastian K. Mitusch, Simon W. Funke
In industry, shape optimization problems are of utter importance when designing structures such as aircraft, automobiles and turbines. For many of these applications, the structure…
A multimesh finite element method for the Navier-Stokes equations based on projection methods
Jørgen S. Dokken, August Johansson, André Massing +1
The multimesh finite element method is a technique for solving partial differential equations on multiple non-matching meshes by enforcing interface conditions using Nitsche's meth…
Can diffusion alone explain brain-wide distribution of a CSF tracer within 24 hours?
Lars Magnus Valnes, Sebastian K. Mitusch, Geir Ringstad +3
The recently proposed glymphatic system suggests that bulk flow is important for clearing waste from the brain, and as such may underlie the development of e.g. Alzheimer's disease…
Shape Optimization using the Finite Element Method on Multiple Meshes
Jorgen S. Dokken, Simon W. Funke, August Johansson +1
An important step in shape optimization with partial differential equation constraints is to adapt the geometry during each optimization iteration. Common strategies are to employ…