George Em Karniadakis

Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

Physics-informed machine learning

The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations

Hidden fluid mechanics: Learning velocity and pressure fields from flow visualizations

Physics-informed neural networks (PINNs) for fluid mechanics: a review

Microflows and Nanoflows : Fundamentals and Simulation

Spectral/hp Element Methods for Computational Fluid Dynamics

Modeling uncertainty in flow simulations via generalized polynomial chaos

High-order splitting methods for the incompressible Navier-Stokes equations

Hidden physics models: Machine learning of nonlinear partial differential equations

Physics-informed neural networks for high-speed flows

NSFnets (Navier-Stokes flow nets): Physics-informed neural networks for the incompressible Navier-Stokes equations