Nicholas H. Nelsen

16 papers A* 1Journal 15

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	A short tour of operator learning theory: Convergence rates, statistical limits, and open questions. CoRR Simone Brugiapaglia, Nicola Rares Franco, Nicholas H. Nelsen
2025	J	`jnl`	Bilevel optimization for learning hyperparameters: Application to solving PDEs and inverse problems with Gaussian processes. CoRR Nicholas H. Nelsen, Houman Owhadi, Andrew M. Stuart, Xianjin Yang, Zongren Zou
2025	J	`jnl`	Extension and neural operator approximation of the electrical impedance tomography inverse map. CoRR Maarten V. de Hoop, Nikola B. Kovachki, Matti Lassas, Nicholas H. Nelsen
2025	J	`jnl`	Hyperparameter optimization for randomized algorithms: a case study on random features. Stat. Comput. Oliver R. A. Dunbar, Nicholas H. Nelsen, Maya Mutic
2025	J	`jnl`	Learning Where to Learn: Training Distribution Selection for Provable OOD Performance. CoRR Nicolas Guerra, Nicholas H. Nelsen, Yunan Yang
2025	J	`jnl`	Operator learning meets inverse problems: A probabilistic perspective. CoRR Nicholas H. Nelsen, Yunan Yang
2024	J	`jnl`	An operator learning perspective on parameter-to-observable maps. CoRR Daniel Zhengyu Huang, Nicholas H. Nelsen, Margaret Trautner
2024	J	`jnl`	Hyperparameter Optimization for Randomized Algorithms: A Case Study for Random Features. CoRR Oliver R. A. Dunbar, Nicholas H. Nelsen, Maya Mutic
2024	J	`jnl`	Operator Learning Using Random Features: A Tool for Scientific Computing. CoRR Nicholas H. Nelsen, Andrew M. Stuart
2024	J	`jnl`	Operator Learning Using Random Features: A Tool for Scientific Computing. SIAM Rev. Nicholas H. Nelsen, Andrew M. Stuart
2023	J	`jnl`	Convergence Rates for Learning Linear Operators from Noisy Data. SIAM/ASA J. Uncertain. Quantification Maarten V. de Hoop, Nikola B. Kovachki, Nicholas H. Nelsen, Andrew M. Stuart
2023	A*	`conf`	Error Bounds for Learning with Vector-Valued Random Features. NeurIPS Samuel Lanthaler, Nicholas H. Nelsen
2023	J	`jnl`	Error Bounds for Learning with Vector-Valued Random Features. CoRR Samuel Lanthaler, Nicholas H. Nelsen
2021	J	`jnl`	Convergence Rates for Learning Linear Operators from Noisy Data. CoRR Maarten V. de Hoop, Nikola B. Kovachki, Nicholas H. Nelsen, Andrew M. Stuart
2021	J	`jnl`	The Random Feature Model for Input-Output Maps between Banach Spaces. SIAM J. Sci. Comput. Nicholas H. Nelsen, Andrew M. Stuart
2020	J	`jnl`	The Random Feature Model for Input-Output Maps between Banach Spaces. CoRR Nicholas H. Nelsen, Andrew M. Stuart