13 citations · 22 across the 8 of their papers we have counts for
3 papers · 1 filter
Enabling Real-Time Training of a Wildfire-to-Smoke Map with Multilinear Operators
Zachary Morrow, Joseph Crockett, John D. Jakeman +1
Wildfires are a major producer of fine particulate matter, impacting human health and the electrical grid. Accurately forecasting smoke impacts over long time scales incorporates f…
SUPN: Shallow Universal Polynomial Networks for Efficient Function Approximation
Zachary Morrow, Michael Penwarden, Brian Chen +3
Deep neural networks (DNNs) and Kolmogorov-Arnold networks (KANs) are flexible function approximators, but their accuracy can require substantial network depth, width, and trainabl…
Kernel Neural Operators (KNOs) for Scalable, Memory-efficient, Geometrically-flexible Operator Learning
Matthew Lowery, John Turnage, Zachary Morrow +4
This paper introduces the Kernel Neural Operator (KNO), a provably convergent operator-learning architecture that utilizes compositions of deep kernel-based integral operators for…