LSTMs

Recurrent Neural Network Architecture Search for Geophysical Emulation

Developing surrogate geophysical models from data is a key research topic in atmospheric andoceanic modeling because of the large computational costs associated with numerical simulationmethods. Researchers have started applying a wide range of …

Time-series learning of latent-space dynamics for reduced-order model closure

We study the performance of long short-term memory networks (LSTMs) and neural ordinarydifferential equations (NODEs) in learning latent-space representations of dynamical equations for anadvection-dominated problem given by the viscous Burgers …