42 citations · 65 across the 19 of their papers we have counts for
4 papers · 1 filter
Non-autoregressive time-series methods for stable parametric reduced-order models
Romit Maulik, Bethany Lusch, Prasanna Balaprakash
Advection-dominated dynamical systems, characterized by partial differential equations, are found in applications ranging from weather forecasting to engineering design where accur…
Recurrent Neural Network Architecture Search for Geophysical Emulation
Romit Maulik, Romain Egele, Bethany Lusch +1
Developing surrogate geophysical models from data is a key research topic in atmospheric and oceanic modeling because of the large computational costs associated with numerical sim…
Neural network representability of fully ionized plasma fluid model closures
Romit Maulik, Nathan A. Garland, Xian-Zhu Tang +1
The closure problem in fluid modeling is a well-known challenge to modelers aiming to accurately describe their system of interest. Over many years, analytic formulations in a wide…
Time-series learning of latent-space dynamics for reduced-order model closure
Romit Maulik, Arvind Mohan, Bethany Lusch +3
We study the performance of long short-term memory networks (LSTMs) and neural ordinary differential equations (NODEs) in learning latent-space representations of dynamical equatio…