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ORCIDNicholas H. Nelsen
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Journal Articles
- 2024
[j3]Nicholas H. Nelsen
, Andrew M. Stuart:
Operator Learning Using Random Features: A Tool for Scientific Computing. SIAM Rev. 66(3): 535-571 (2024)- 2023
- [j2]Maarten V. de Hoop, Nikola B. Kovachki, Nicholas H. Nelsen, Andrew M. Stuart:
Convergence Rates for Learning Linear Operators from Noisy Data. SIAM/ASA J. Uncertain. Quantification 11(2): 480-513 (2023) - 2021
- [j1]Nicholas H. Nelsen, Andrew M. Stuart:
The Random Feature Model for Input-Output Maps between Banach Spaces. SIAM J. Sci. Comput. 43(5): A3212-A3243 (2021)
Conference and Workshop Papers
- 2023
- [c1]Samuel Lanthaler, Nicholas H. Nelsen:
Error Bounds for Learning with Vector-Valued Random Features. NeurIPS 2023
Informal and Other Publications
- 2024
- [i6]Daniel Zhengyu Huang, Nicholas H. Nelsen, Margaret Trautner:
An operator learning perspective on parameter-to-observable maps. CoRR abs/2402.06031 (2024) - [i5]Oliver R. A. Dunbar, Nicholas H. Nelsen, Maya Mutic:
Hyperparameter Optimization for Randomized Algorithms: A Case Study for Random Features. CoRR abs/2407.00584 (2024) - [i4]Nicholas H. Nelsen, Andrew M. Stuart:
Operator Learning Using Random Features: A Tool for Scientific Computing. CoRR abs/2408.06526 (2024) - 2023
- [i3]Samuel Lanthaler, Nicholas H. Nelsen:
Error Bounds for Learning with Vector-Valued Random Features. CoRR abs/2305.17170 (2023) - 2021
- [i2]Maarten V. de Hoop, Nikola B. Kovachki, Nicholas H. Nelsen, Andrew M. Stuart:
Convergence Rates for Learning Linear Operators from Noisy Data. CoRR abs/2108.12515 (2021) - 2020
- [i1]Nicholas H. Nelsen, Andrew M. Stuart:
The Random Feature Model for Input-Output Maps between Banach Spaces. CoRR abs/2005.10224 (2020)
Coauthor Index
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