30 citations · 48 across the 11 of their papers we have counts for
4 papers · 1 filter
A Black Box Variational Inference Scheme for Inverse Problems with Demanding Physics-Based Models
G. Robalo Rei, C. P. Schmidt, J. Nitzler +2
Bayesian methods are particularly effective for addressing inverse problems due to their ability to manage uncertainties inherent in the inference process. However, employing these…
Multi-Physics-Enhanced Bayesian Inverse Analysis: Information Gain from Additional Fields
Lea J. Haeusel, Jonas Nitzler, Lea J. Köglmeier +1
Inverse analysis, such as model calibration, often suffers from a lack of informative data in complex real-world scenarios. The standard remedy, designing new experimental setups,…
QUEENS: An Open-Source Python Framework for Solver-Independent Analyses of Large-Scale Computational Models
Jonas Biehler, Jonas Nitzler, Sebastian Brandstaeter +7
A growing challenge in research and industrial engineering applications is the need for repeated, systematic analysis of large-scale computational models, for example, patient-spec…
Efficient Bayesian multi-fidelity inverse analysis for expensive and non-differentiable physics-based simulations in high stochastic dimensions
Jonas Nitzler, Bugrahan Z. Temür, Phaedon-Stelios Koutsourelakis +1
High-dimensional Bayesian inverse analysis (dim >> 100) is mostly unfeasible for computationally demanding, nonlinear physics-based high-fidelity (HF) models. Usually, the use of m…