56 citations · 117 across the 16 of their papers we have counts for
3 papers · 1 filter
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…
Bayesian Deep Learning for Partial Differential Equation Parameter Discovery with Sparse and Noisy Data
Christophe Bonneville, Christopher J. Earls
Scientific machine learning has been successfully applied to inverse problems and PDE discovery in computational physics. One caveat concerning current methods is the need for larg…
Analysis of heterogeneous computing approaches to simulating heat transfer in heterogeneous material
Andrew Loeb, Christopher Earls
The simulation of heat flow through heterogeneous material is important for the design of structural and electronic components. Classical analytical solutions to the heat equation…