activity
20232026
most citedFinite elements for Matérn-type random fields: Uncertainty in computational mechanics and design optimization

9 citations · 11 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CE2026

Device-Induced Thrombus Formation in Cerebral Aneurysms: Linking Patient-Specific Clot Modeling and Functional Occlusion to Virtual Angiographic Assessment

Fabian Holzberger, Struan Hume, Markus Muhr +2

Endovascular treatment of cerebral aneurysms aims to achieve functional occlusion and isolation of the aneurysm sac from bloodflow. In clinical practice, treatment success is asses…

math.NA2024★ 1 cited

Regularity Analysis and High-Order Time Stepping Scheme for Quasilinear Subdiffusion

Bangti Jin, Qimeng Quan, Barbara Wohlmuth +1

In this work, we investigate a quasilinear subdiffusion model which involves a fractional derivative of order in time and a nonlinear diffusion coefficient. First, usi…

cs.CE2024★ 1 cited

Calibration of stochastic, agent-based neuron growth models with Approximate Bayesian Computation

Tobias Duswald, Lukas Breitwieser, Thomas Thorne +2

Understanding how genetically encoded rules drive and guide complex neuronal growth processes is essential to comprehending the brain's architecture, and agent-based models (ABMs)…

cs.CE2024★ 9 cited

Finite elements for Matérn-type random fields: Uncertainty in computational mechanics and design optimization

Tobias Duswald, Brendan Keith, Boyan Lazarov +2

This work highlights an approach for incorporating realistic uncertainties into scientific computing workflows based on finite elements, focusing on applications in computational m…

math.AP2023

Directional flow in perivascular networks: Mixed finite elements for reduced-dimensional models on graphs

Ingeborg G. Gjerde, Miroslav Kuchta, Marie E. Rognes +1

The flow of cerebrospinal fluid through the perivascular spaces of the brain is believed to play a crucial role in eliminating toxic waste proteins. While the driving forces of thi…