1 code implementation • 8 Feb 2024 • Daniel Zhengyu Huang, Nicholas H. Nelsen, Margaret Trautner
Computationally efficient surrogates for parametrized physical models play a crucial role in science and engineering.
1 code implementation • NeurIPS 2023 • Samuel Lanthaler, Nicholas H. Nelsen
This paper provides a comprehensive error analysis of learning with vector-valued random features (RF).
no code implementations • 27 Aug 2021 • Maarten V. de Hoop, Nikola B. Kovachki, Nicholas H. Nelsen, Andrew M. Stuart
This paper studies the learning of linear operators between infinite-dimensional Hilbert spaces.
1 code implementation • 20 May 2020 • Nicholas H. Nelsen, Andrew M. Stuart
Well known to the machine learning community, the random feature model is a parametric approximation to kernel interpolation or regression methods.