activity
20192026
most citedNonlinear Approximation and (Deep) ReLU Networks

102 citations · 106 across the 9 of their papers we have counts for

collaborators

9 papers

math.NA2026

Constrained Kolmogorov widths

Ronald DeVore, Guergana Petrova, Jonathan W. Siegel +1

The main theme of approximation theory is to understand how well a general function can be approximated by a simpler function such as a polynomial or spline. In many applic…

math.NA2026

Sampling and reconstruction of convex functions

Andrea Bonito, Albert Cohen, Wolfgang Dahmen +3

We discuss optimal recovery for classes of multivariate convex functions from given point samples, as well as the sampling numbers of these classes, corresponding to optimal sample…

math.ST2025

Optimal Recovery Meets Minimax Estimation

Ronald DeVore, Robert D. Nowak, Rahul Parhi +2

A fundamental problem in statistics and machine learning is to estimate a function from possibly noisy observations of its point samples. The goal is to design a numerical algo…

math.NA2024

A note on best n-term approximation for generalized Wiener classes

Ronald DeVore, Guergana Petrova, Przemyslaw Wojtaszczyk

We determine the best n-term approximation of generalized Wiener model classes in a Hilbert space . This theory is then applied to several special cases.

math.NA2024

Convergence and error control of consistent PINNs for elliptic PDEs

Andrea Bonito, Ronald DeVore, Guergana Petrova +1

We provide an a priori analysis of collocation methods for solving elliptic boundary value problems. They begin with information in the form of point values of the data and utilize…

stat.ML2023★ 3 cited

Weighted variation spaces and approximation by shallow ReLU networks

Ronald DeVore, Robert D. Nowak, Rahul Parhi +1

We investigate the approximation of functions on a bounded domain by the outputs of single-hidden-layer ReLU neural networks of width . This form of…