105 citations · 152 across the 16 of their papers we have counts for
3 papers · 1 filter
Improved multifidelity Monte Carlo estimators based on normalizing flows and dimensionality reduction techniques
Andrea Zanoni, Gianluca Geraci, Matteo Salvador +3
We study the problem of multifidelity uncertainty propagation for computationally expensive models. In particular, we consider the general setting where the high-fidelity and low-f…
A Probabilistic Neural Twin for Treatment Planning in Peripheral Pulmonary Artery Stenosis
John D. Lee, Jakob Richter, Martin R. Pfaller +8
The substantial computational cost of high-fidelity models in numerical hemodynamics has, so far, relegated their use mainly to offline treatment planning. New breakthroughs in dat…
InVAErt networks: a data-driven framework for model synthesis and identifiability analysis
Guoxiang Grayson Tong, Carlos A. Sing Long, Daniele E. Schiavazzi
Use of generative models and deep learning for physics-based systems is currently dominated by the task of emulation. However, the remarkable flexibility offered by data-driven arc…