3 papers
math.NA2026
Learning solution operators of PDEs with sparse approximation methods
Sebastian Neumayer, Daniel Potts, Fabian Taubert
We investigate the approximation of solution operators for partial differential equations (PDEs) using sparse high-dimensional techniques. Building on a dimension-incremental frame…
math.NA2024
An approach to discrete operator learning based on sparse high-dimensional approximation
Daniel Potts, Fabian Taubert
We present a dimension-incremental method for function approximation in bounded orthonormal product bases to learn the solutions of various differential equations. Therefore, we de…
math.NA2023
Nonlinear Approximation with Subsampled Rank-1 Lattices
Felix Bartel, Fabian Taubert
In this paper we approximate high-dimensional functions by sparse trigonometric polynomials based on function evaluations. Recently it was shown th…