3 papers
stat.ME2026
Sample correlation adjustments for robust Multi-fidelity Monte Carlo under limited pilot sampling
Michael Stanley, Thomas Coons, Geoffrey Bomarito +3
Multi-fidelity Monte Carlo (MFMC) is a variance reduction method that leverages a multi-fidelity ensemble of models of varying cost and accuracy levels. Constructing an MFMC estima…
cs.LG2026
Constraint-Aware Flow Matching: Decision Aligned End-to-End Training for Constrained Sampling
Jacob K. Christopher, James E. Warner, Ferdinando Fioretto
Deep generative models provide state-of-the-art performance across a wide array of applications, with recent studies showing increasing applicability for science and engineering. D…
stat.CO2026
Automated Model Tuning for Multifidelity Uncertainty Propagation in Trajectory Simulation
James E. Warner, Geoffrey F. Bomarito, Gianluca Geraci +1
Multifidelity uncertainty propagation combines the efficiency of low-fidelity models with the accuracy of a high-fidelity model to construct statistical estimators of quantities of…