3 papers
physics.comp-ph2019
Real-Time Reduced-Order Modeling of Stochastic Partial Differential Equations via Time-Dependent Subspaces
Prerna Patil, Hessam Babaee
We present a new methodology for the real-time reduced-order modeling of stochastic partial differential equations called the dynamically/bi-orthonormal (DBO) decomposition. In thi…
physics.flu-dyn2018
Deep Learning of Turbulent Scalar Mixing
Maziar Raissi, Hessam Babaee, Peyman Givi
Based on recent developments in physics-informed deep learning and deep hidden physics models, we put forth a framework for discovering turbulence models from scattered and potenti…
stat.ML2017
Parametric Gaussian Process Regression for Big Data
Maziar Raissi
This work introduces the concept of parametric Gaussian processes (PGPs), which is built upon the seemingly self-contradictory idea of making Gaussian processes parametric. Paramet…