On efficient algorithms for computing near-best polynomial approximations to high-dimensional, Hilbert-valued functions from limited samples

25 March 2022

Papers citing "On efficient algorithms for computing near-best polynomial approximations to high-dimensional, Hilbert-valued functions from limited samples"

6 / 6 papers shown

Title
Can stable and accurate neural networks be computed? -- On the barriers of deep learning and Smale's 18th problem Matthew J. Colbrook Vegard Antun A. Hansen 93 133 0 20 Jan 2021
Deep Neural Networks Are Effective At Learning High-Dimensional Hilbert-Valued Functions From Limited Data Ben Adcock Simone Brugiapaglia N. Dexter S. Moraga 64 29 0 11 Dec 2020
Automatic selection of basis-adaptive sparse polynomial chaos expansions for engineering applications Nora Lüthen S. Marelli Bruno Sudret 22 28 0 10 Sep 2020
Sparse Polynomial Chaos Expansions: Literature Survey and Benchmark Nora Lüthen S. Marelli Bruno Sudret 34 152 0 04 Feb 2020
Sparse Polynomial Chaos Expansions via Compressed Sensing and D-optimal Design Paul Diaz Alireza Doostan Jerrad Hampton 33 100 0 29 Dec 2017
Enhancing Sparsity of Hermite Polynomial Expansions by Iterative Rotations Xiu Yang H. Lei Nathan A. Baker Guang Lin 33 53 0 14 Jun 2015