105 citations · 152 across the 16 of their papers we have counts for
4 papers · 1 filter
Assessing the performance of correlation-based multi-fidelity neural emulators
Cristian J. Villatoro, Gianluca Geraci, Daniele E. Schiavazzi
Outer loop tasks such as optimization, uncertainty quantification or inference can easily become intractable when the underlying high-fidelity model is computationally expensive. S…
On the performance of multi-fidelity and reduced-dimensional neural emulators for inference of physiological boundary conditions
Chloe H. Choi, Andrea Zanoni, Daniele E. Schiavazzi +1
Solving inverse problems in cardiovascular modeling is particularly challenging due to the high computational cost of running high-fidelity simulations. In this work, we focus on B…
Enabling stratified sampling in high dimensions via nonlinear dimensionality reduction
Gianluca Geraci, Daniele E. Schiavazzi, Andrea Zanoni
We consider the problem of propagating the uncertainty from a possibly large number of random inputs through a computationally expensive model. Stratified sampling is a well-known…
Rule-based and reinforcement-learning policies for resource allocation in a pediatric echo lab: a simulation study
Bozhi Sun, Seda Tierney, Jeffrey A. Feinstein +3
Scheduling echocardiographic examinations in a hospital setting presents significant challenges due to non-deterministic factors such as patient no-shows, variable arrival times, a…