Nick C. Dexter - researchr alias

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Viewing Publication 1 - 7 from 7

2023

An Adaptive Sampling and Domain Learning Strategy for Multivariate Function Approximation on Unknown DomainsBen Adcock, Juan M. Cardenas, Nick C. Dexter. siamsc, 45(1):200, February 2023. [doi]

CS4ML: A general framework for active learning with arbitrary data based on Christoffel functionsJuan M. Cardenas, Ben Adcock, Nick C. Dexter. nips 2023: [doi]

2021

Deep Neural Networks Are Effective At Learning High-Dimensional Hilbert-Valued Functions From Limited DataBen Adcock, Simone Brugiapaglia, Nick C. Dexter, Sebastian Moraga. msml 2021: 1-36 [doi]

The Gap between Theory and Practice in Function Approximation with Deep Neural NetworksBen Adcock, Nick C. Dexter. simods, 3(2):624-655, 2021. [doi]

Improved Recovery Guarantees and Sampling Strategies for TV Minimization in Compressive ImagingBen Adcock, Nick C. Dexter, Qinghong Xu. siamis, 14(3):1149-1183, 2021. [doi]

2018

Polynomial approximation via compressed sensing of high-dimensional functions on lower setsAbdellah Chkifa, Nick C. Dexter, Hoang Tran, Clayton G. Webster. moc, 87(311):1415-1450, 2018. [doi]

2016

Explicit cost bounds of stochastic Galerkin approximations for parameterized PDEs with random coefficientsNick C. Dexter, Clayton G. Webster, Guannan Zhang. cma, 71(11):2231-2256, 2016. [doi]

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