3 papers
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
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…
cs.CE2024
Dynamic Learning Rate Decay for Stochastic Variational Inference
Maximilian Dinkel, Gil Robalo Rei, Wolfgang A. Wall
Like many optimization algorithms, Stochastic Variational Inference (SVI) is sensitive to the choice of the learning rate. If the learning rate is too small, the optimization proce…