Published September 2022 | Version v1
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Supplementary material - Stochastic modeling of inhomogeneities in the aortic wall and uncertainty quantification using a Bayesian encoder-decoder surrogate, Comput Methods Appl Mech Eng, 2022

  • 1. ROR icon Graz University of Technology
  • 1. ROR icon Graz University of Technology
  • 2. ROR icon Essen University Hospital
  • 3. ROR icon Norwegian University of Science and Technology

Description

Supplementary material

Ranftl et al.: Stochastic modeling of inhomogeneities in the aortic wall and uncertainty quantification using a Bayesian encoder-decoder surrogate, Comput Methods Appl Mech Eng, 2022

Files

Supplementary material - Stochastic modeling of inhomogeneities in the aortic wall and uncertainty quantification using a Bayesian encoder-decoder surrogate.zip
Created:
September 14, 2022
Modified:
September 14, 2022