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cs.LG2022★ 3 cited
PDE-LEARN: Using Deep Learning to Discover Partial Differential Equations from Noisy, Limited Data
Robert Stephany, Christopher Earls
In this paper, we introduce PDE-LEARN, a novel deep learning algorithm that can identify governing partial differential equations (PDEs) directly from noisy, limited measurements o…
math.NA2022★ 3 cited
Principled interpolation of Green's functions learned from data
Harshwardhan Praveen, Nicolas Boulle, Christopher Earls
We present a data-driven approach to mathematically model physical systems whose governing partial differential equations are unknown, by learning their associated Green's function…