Nick C. Dexter

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 25

Top Topics

High Dimensions

Adaptive Sampling

Function Approximation

Top Venues

SIAM J. Math. Data Sci.

Comput. Math. Appl.

Publications

Ben Adcock, Nick C. Dexter, Sebastian Moraga
Optimal deep learning of holomorphic operators between Banach spaces. CoRR (2024)
Ben Adcock, Simone Brugiapaglia, Nick C. Dexter, Sebastian Moraga
Learning smooth functions in high dimensions: from sparse polynomials to deep neural networks. CoRR (2024)
Simone Brugiapaglia, Nick C. Dexter, Samir Karam, Weiqi Wang
Physics-informed deep learning and compressive collocation for high-dimensional diffusion-reaction equations: practical existence theory and numerics. CoRR (2024)
Ben Adcock, Nick C. Dexter, Sebastian Moraga
Optimal approximation of infinite-dimensional holomorphic functions II: recovery from i.i.d. pointwise samples. CoRR (2023)
Ben Adcock, Juan M. Cardenas, Nick C. Dexter
CS4ML: A general framework for active learning with arbitrary data based on Christoffel functions. CoRR (2023)
Ben Adcock, Nick C. Dexter, Sebastian Moraga
Optimal approximation of infinite-dimensional holomorphic functions. CoRR (2023)
Ben Adcock, Juan M. Cardenas, Nick C. Dexter
An Adaptive Sampling and Domain Learning Strategy for Multivariate Function Approximation on Unknown Domains. SIAM J. Sci. Comput. 45 (1) (2023)
Ben Adcock, Juan M. Cardenas, Nick C. Dexter
A unified framework for learning with nonlinear model classes from arbitrary linear samples. CoRR (2023)
Juan M. Cardenas, Ben Adcock, Nick C. Dexter
CS4ML: A general framework for active learning with arbitrary data based on Christoffel functions. NeurIPS (2023)
Ben Adcock, Juan M. Cardenas, Nick C. Dexter, Sebastian Moraga
Towards optimal sampling for learning sparse approximation in high dimensions. CoRR (2022)
Ben Adcock, Simone Brugiapaglia, Nick C. Dexter, Sebastian Moraga
Near-optimal learning of Banach-valued, high-dimensional functions via deep neural networks. CoRR (2022)
Ben Adcock, Juan M. Cardenas, Nick C. Dexter
CAS4DL: Christoffel Adaptive Sampling for function approximation via Deep Learning. CoRR (2022)
Ben Adcock, Juan M. Cardenas, Nick C. Dexter
An Adaptive sampling and domain learning strategy for multivariate function approximation on unknown domains. CoRR (2022)
Ben Adcock, Simone Brugiapaglia, Nick C. Dexter, Sebastian Moraga
On efficient algorithms for computing near-best polynomial approximations to high-dimensional, Hilbert-valued functions from limited samples. CoRR (2022)
Ben Adcock, Simone Brugiapaglia, Nick C. Dexter, Sebastian Moraga
Deep Neural Networks Are Effective At Learning High-Dimensional Hilbert-Valued Functions From Limited Data. MSML (2021)
Ben Adcock, Nick C. Dexter
The Gap between Theory and Practice in Function Approximation with Deep Neural Networks. SIAM J. Math. Data Sci. 3 (2) (2021)
Ben Adcock, Simone Brugiapaglia, Nick C. Dexter, Sebastian Moraga
Learning High-Dimensional Hilbert-Valued Functions With Deep Neural Networks From Limited Data. AAAI Spring Symposium: MLPS (2021)
Hooman Zabeti, Nick C. Dexter, Amir Hosein Safari, Nafiseh Sedaghat, Maxwell W. Libbrecht, Leonid Chindelevitch
INGOT-DR: an interpretable classifier for predicting drug resistance in M. tuberculosis. Algorithms Mol. Biol. 16 (1) (2021)
Ben Adcock, Nick C. Dexter, Qinghong Xu
Improved Recovery Guarantees and Sampling Strategies for TV Minimization in Compressive Imaging. SIAM J. Imaging Sci. 14 (3) (2021)
Hooman Zabeti, Nick C. Dexter, Amirhossein Safari, Nafiseh Sedaghat, Maxwell W. Libbrecht, Leonid Chindelevitch
An Interpretable Classification Method for Predicting Drug Resistance in M. Tuberculosis. WABI (2020)
Ben Adcock, Nick C. Dexter
The gap between theory and practice in function approximation with deep neural networks. CoRR (2020)
Ben Adcock, Simone Brugiapaglia, Nick C. Dexter, Sebastian Moraga
Deep Neural Networks Are Effective At Learning High-Dimensional Hilbert-Valued Functions From Limited Data. CoRR (2020)
Ben Adcock, Nick C. Dexter, Qinghong Xu
Improved recovery guarantees and sampling strategies for TV minimization in compressive imaging. CoRR (2020)
Abdellah Chkifa, Nick C. Dexter, Hoang Tran, Clayton G. Webster
Polynomial approximation via compressed sensing of high-dimensional functions on lower sets. Math. Comput. 87 (311) (2018)
Nick C. Dexter, Clayton G. Webster, Guannan Zhang
Explicit cost bounds of stochastic Galerkin approximations for parameterized PDEs with random coefficients. Comput. Math. Appl. 71 (11) (2016)