The physics-informed neural network (PINN) is able to identify partial differential equation
(PDE) coefficients which are constant across the space directly from physical …

Observable dynamics, such as waves propagating on a surface, are generally governed by
partial differential equations (PDEs), which are determined by the physical properties of the …

The physics-informed neural network (PINN) can recover partial differential equation (PDE)
coefficients that remain constant throughout the spatial domain directly from measurements …

The physics-informed neural network (PINN) is capable of recovering partial differential
equation (PDE) coefficients that remain constant throughout the spatial domain directly from …

We propose a physics-informed neural network (PINN) based approach that can recover the
spatially-varying acoustic properties including sound speed and attenuation via partial …

The dynamics of many natural phenomena are described by partial differential equations
(PDEs). With the rise in computing resources, machine learning methods for PDE recovery …