13 citations · 24 across the 5 of their papers we have counts for
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cs.LG2021★ 6 cited
CIRA Guide to Custom Loss Functions for Neural Networks in Environmental Sciences -- Version 1
Imme Ebert-Uphoff, Ryan Lagerquist, Kyle Hilburn +5
Neural networks are increasingly used in environmental science applications. Furthermore, neural network models are trained by minimizing a loss function, and it is crucial to choo…
math.NA2021
Simple finite elements and multigrid for efficient mass-consistent wind downscaling in a coupled fire-atmosphere model
J. Mandel, A. Farguell, A. K. Kochanski +2
We present a simple finite element formulation of mass-consistent approximation, and a fast multigrid iterative method with adaptive semicoarsening, which maintains the convergence…