16 citations · 31 across the 13 of their papers we have counts for
7 papers · 1 filter
Learning to Bias: Machine Learning-Enhanced Particle Filters
Apoorv Srivastava, Eric Darve
Sequential inference estimates latent states from noisy and incomplete observations. Particle Filters (PFs), a class of Monte Carlo methods based on importance sampling, provide a…
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…
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…
Coincident Learning for Unsupervised Anomaly Detection
Ryan Humble, Zhe Zhang, Finn O'Shea +2
Anomaly detection is an important task for complex systems (e.g., industrial facilities, manufacturing, large-scale science experiments), where failures in a sub-system can lead to…
Variational encoder geostatistical analysis (VEGAS) with an application to large scale riverine bathymetry
Mojtaba Forghani, Yizhou Qian, Jonghyun Lee +4
Estimation of riverbed profiles, also known as bathymetry, plays a vital role in many applications, such as safe and efficient inland navigation, prediction of bank erosion, land s…
Deep learning-based fast solver of the shallow water equations
Mojtaba Forghani, Yizhou Qian, Jonghyun Lee +4
Fast and reliable prediction of river flow velocities is important in many applications, including flood risk management. The shallow water equations (SWEs) are commonly used for t…
Application of deep learning to large scale riverine flow velocity estimation
Mojtaba Forghani, Yizhou Qian, Jonghyun Lee +4
Fast and reliable prediction of riverine flow velocities is important in many applications, including flood risk management. The shallow water equations (SWEs) are commonly used fo…