27 citations · 34 across the 7 of their papers we have counts for
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cs.LG2023★ 2 cited
Learning Reduced-Order Models for Cardiovascular Simulations with Graph Neural Networks
Luca Pegolotti, Martin R. Pfaller, Natalia L. Rubio +4
Reduced-order models based on physics are a popular choice in cardiovascular modeling due to their efficiency, but they may experience reduced accuracy when working with anatomies…
cs.LG2023
Physics-based parameterized neural ordinary differential equations: prediction of laser ignition in a rocket combustor
Yizhou Qian, Jonathan Wang, Quentin Douasbin +1
In this work, we present a novel physics-based data-driven framework for reduced-order modeling of laser ignition in a model rocket combustor based on parameterized neural ordinary…