collaborators

6 papers

cs.CE2026

Scalable High-Dimensional Bayesian Field Reconstruction with Finite Elements: Application to 3D Porous Media Flow

Jonas Nitzler, Maximilian Bergbauer, Phaedon-Stelios Koutsourelakis +1

We present a unified, finite-element-native variational inference framework for very high-dimensional Bayesian spatial field reconstruction in physics-based problems governed by pa…

cs.CE2026

Multi-Agent Framework Leveraging Knowledge Graphs for Virtual Commissioning Models

Max Diekmann, Jonas Nitzler, Jan Fischer +2

Virtual commissioning models (VCMs) of discrete manufacturing systems are used to validate automation behavior before physical deployment, but creating and maintaining them remains…

cs.CE2025

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,…

cs.CE2025

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…

cs.CE2025

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…

cs.CE2025

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…