92 citations · 280 across the 15 of their papers we have counts for
4 papers · 1 filter
Capturing missing physics in climate model parameterizations using neural differential equations
Ali Ramadhan, John Marshall, Andre Souza +8
We explore how neural differential equations (NDEs) may be trained on highly resolved fluid-dynamical models of unresolved scales providing an ideal framework for data-driven param…
A machine learning aided global diagnostic and comparative tool to assess effect of quarantine control in Covid-19 spread
Raj Dandekar, Chris Rackauckas, George Barbastathis
We have developed a globally applicable diagnostic Covid-19 model by augmenting the classical SIR epidemiological model with a neural network module. Our model does not rely upon p…
Signal Enhancement for Magnetic Navigation Challenge Problem
Albert R. Gnadt, Joseph Belarge, Aaron Canciani +10
Harnessing the magnetic field of the Earth for navigation has shown promise as a viable alternative to other navigation systems. A magnetic navigation system collects its own magne…
Universal Differential Equations for Scientific Machine Learning
Christopher Rackauckas, Yingbo Ma, Julius Martensen +6
In the context of science, the well-known adage "a picture is worth a thousand words" might well be "a model is worth a thousand datasets." In this manuscript we introduce the SciM…