56 citations · 117 across the 16 of their papers we have counts for
4 papers · 1 filter
PDE-READ: Human-readable Partial Differential Equation Discovery using Deep Learning
Robert Stephany, Christopher Earls
PDE discovery shows promise for uncovering predictive models of complex physical systems but has difficulty when measurements are sparse and noisy. We introduce a new approach for…
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…
Data-driven discovery of Green's functions with human-understandable deep learning
Nicolas Boullé, Christopher J. Earls, Alex Townsend
There is an opportunity for deep learning to revolutionize science and technology by revealing its findings in a human interpretable manner. To do this, we develop a novel data-dri…
A new engineering theory describing oblique free surface impact by flexible plates
Wensi Wu, Christopher Earls
Consideration of slamming loads within the structural design of planning hulls is of critical importance in ensuring adequate structural performance in order to avoid potential cat…