2 citations · 2 across the 1 of their papers we have counts for
4 papers
Data-driven discovery of Green's functions
Nicolas Boullé
Discovering hidden partial differential equations (PDEs) and operators from data is an important topic at the frontier between machine learning and numerical analysis. This doctora…
An optimal complexity spectral method for Navier--Stokes simulations in the ball
Nicolas Boullé, Jonasz Słomka, Alex Townsend
We develop a spectral method for solving the incompressible generalized Navier--Stokes equations in the ball with no-flux and prescribed slip boundary conditions. The algorithm ach…
Rational neural networks
Nicolas Boullé, Yuji Nakatsukasa, Alex Townsend
We consider neural networks with rational activation functions. The choice of the nonlinear activation function in deep learning architectures is crucial and heavily impacts the pe…
Computing with functions in the ball
Nicolas Boullé, Alex Townsend
A collection of algorithms in object-oriented MATLAB is described for numerically computing with smooth functions defined on the unit ball in the Chebfun software. Functions are nu…