1 citations · 1 across the 2 of their papers we have counts for
2 papers
stat.ML2024
Maximum a Posteriori Estimation for Linear Structural Dynamics Models Using Bayesian Optimization with Rational Polynomial Chaos Expansions
Felix Schneider, Iason Papaioannou, Bruno Sudret +1
Bayesian analysis enables combining prior knowledge with measurement data to learn model parameters. Commonly, one resorts to computing the maximum a posteriori (MAP) estimate, whe…
math.DS2024★ 1 cited
Inconsistency Removal of Reduced Bases in Parametric Model Order Reduction by Matrix Interpolation using Adaptive Sampling and Clustering
Sebastian Resch-Schopper, Romain Rumpler, Gerhard Müller
Parametric model order reduction by matrix interpolation allows for efficient prediction of the behavior of dynamic systems without requiring knowledge about the underlying paramet…