The Random Feature Model for Input-Output Maps between Banach Spaces. - Nicholas H. Nelsen; Andrew M. Stuart (SIAM J. Sci. Comput., 2021)

Error Bounds for Learning with Vector-Valued Random Features. - Samuel Lanthaler; Nicholas H. Nelsen (NeurIPS, 2023)

Convergence Rates for Learning Linear Operators from Noisy Data. - Maarten V. de Hoop; Nikola B. Kovachki; Nicholas H. Nelsen; Andrew M. Stuart (SIAM/ASA J. Uncertain. Quantification, 2023)

An operator learning perspective on parameter-to-observable maps. - Daniel Zhengyu Huang; Nicholas H. Nelsen; Margaret Trautner (CoRR, 2024)

Operator Learning Using Random Features: A Tool for Scientific Computing. - Nicholas H. Nelsen; Andrew M. Stuart (SIAM Rev., 2024)

Learning Where to Learn: Training Distribution Selection for Provable OOD Performance. - Nicolas Guerra; Nicholas H. Nelsen; Yunan Yang (CoRR, 2025)

Hyperparameter optimization for randomized algorithms: a case study on random features. - Oliver R. A. Dunbar; Nicholas H. Nelsen; Maya Mutic (Stat. Comput., 2025)