102 citations · 246 across the 25 of their papers we have counts for
4 papers · 1 filter
Linking Machine Learning with Multiscale Numerics: Data-Driven Discovery of Homogenized Equations
Hassan Arbabi, Judith E. Bunder, Giovanni Samaey +2
The data-driven discovery of partial differential equations (PDEs) consistent with spatiotemporal data is experiencing a rebirth in machine learning research. Training deep neural…
Equation-free patch scheme for efficient computational homogenisation via self-adjoint coupling
J. E. Bunder, I. G. Kevrekidis, A. J. Roberts
Equation-free macroscale modelling is a systematic and rigorous computational methodology for efficiently predicting the dynamics of a microscale system at a desired macroscale sys…
A multiscale scheme accurately simulates macroscale shocks in an equation-free framework
John Maclean, J. E. Bunder, A. J. Roberts +1
Scientists and engineers often create accurate, trustworthy, computational simulation schemes - but all too often these are too computationally expensive to execute over the time o…
A toolbox of Equation-Free functions in Matlab\Octave for efficient system level simulation
John Maclean, J. E. Bunder, A. J. Roberts
The `equation-free toolbox' empowers the computer-assisted analysis of complex, multiscale systems. Its aim is to enable you to immediately use microscopic simulators to perform ma…