Nick C. Dexter

30 papers A* 3C 1Journal 24Unranked 2

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Near-optimal learning of Banach-valued, high-dimensional functions via deep neural networks. Neural Networks Ben Adcock, Simone Brugiapaglia, Nick C. Dexter, Sebastian Moraga
2025	J	`jnl`	Optimal approximation of infinite-dimensional holomorphic functions II: Recovery from i.i.d. pointwise samples. J. Complex. Ben Adcock, Nick C. Dexter, Sebastian Moraga
2025	J	`jnl`	Physics-Informed Deep Learning and Compressive Collocation for High-Dimensional Diffusion-Reaction Equations: Practical Existence Theory and Numerics. J. Mach. Learn. Res. Simone Brugiapaglia, Nick C. Dexter, Samir Karam, Weiqi Wang
2024	A*	`conf`	A Unified Framework for Learning with Nonlinear Model Classes from Arbitrary Linear Samples. ICML Ben Adcock, Juan M. Cardenas, Nick C. Dexter
2024	J	`jnl`	Learning smooth functions in high dimensions: from sparse polynomials to deep neural networks. CoRR Ben Adcock, Simone Brugiapaglia, Nick C. Dexter, Sebastian Moraga
2024	A*	`conf`	Optimal deep learning of holomorphic operators between Banach spaces. NeurIPS Ben Adcock, Nick C. Dexter, Sebastian Moraga Scheuermann
2024	J	`jnl`	Optimal deep learning of holomorphic operators between Banach spaces. CoRR Ben Adcock, Nick C. Dexter, Sebastian Moraga
2024	J	`jnl`	Physics-informed deep learning and compressive collocation for high-dimensional diffusion-reaction equations: practical existence theory and numerics. CoRR Simone Brugiapaglia, Nick C. Dexter, Samir Karam, Weiqi Wang
2023	J	`jnl`	A unified framework for learning with nonlinear model classes from arbitrary linear samples. CoRR Ben Adcock, Juan M. Cardenas, Nick C. Dexter
2023	J	`jnl`	An Adaptive Sampling and Domain Learning Strategy for Multivariate Function Approximation on Unknown Domains. SIAM J. Sci. Comput. Ben Adcock, Juan M. Cardenas, Nick C. Dexter
2023	A*	`conf`	CS4ML: A general framework for active learning with arbitrary data based on Christoffel functions. NeurIPS Juan M. Cardenas, Ben Adcock, Nick C. Dexter
2023	J	`jnl`	CS4ML: A general framework for active learning with arbitrary data based on Christoffel functions. CoRR Ben Adcock, Juan M. Cardenas, Nick C. Dexter
2023	J	`jnl`	Optimal approximation of infinite-dimensional holomorphic functions II: recovery from i.i.d. pointwise samples. CoRR Ben Adcock, Nick C. Dexter, Sebastian Moraga
2023	J	`jnl`	Optimal approximation of infinite-dimensional holomorphic functions. CoRR Ben Adcock, Nick C. Dexter, Sebastian Moraga
2022	J	`jnl`	An Adaptive sampling and domain learning strategy for multivariate function approximation on unknown domains. CoRR Ben Adcock, Juan M. Cardenas, Nick C. Dexter
2022	J	`jnl`	CAS4DL: Christoffel Adaptive Sampling for function approximation via Deep Learning. CoRR Ben Adcock, Juan M. Cardenas, Nick C. Dexter
2022	J	`jnl`	Near-optimal learning of Banach-valued, high-dimensional functions via deep neural networks. CoRR Ben Adcock, Simone Brugiapaglia, Nick C. Dexter, Sebastian Moraga
2022	J	`jnl`	On efficient algorithms for computing near-best polynomial approximations to high-dimensional, Hilbert-valued functions from limited samples. CoRR Ben Adcock, Simone Brugiapaglia, Nick C. Dexter, Sebastian Moraga
2022	J	`jnl`	Towards optimal sampling for learning sparse approximation in high dimensions. CoRR Ben Adcock, Juan M. Cardenas, Nick C. Dexter, Sebastian Moraga
2021	—	`conf`	Deep Neural Networks Are Effective At Learning High-Dimensional Hilbert-Valued Functions From Limited Data. MSML Ben Adcock, Simone Brugiapaglia, Nick C. Dexter, Sebastian Moraga
2021	J	`jnl`	INGOT-DR: an interpretable classifier for predicting drug resistance in M. tuberculosis. Algorithms Mol. Biol. Hooman Zabeti, Nick C. Dexter, Amir Hosein Safari, Nafiseh Sedaghat, Maxwell W. Libbrecht, Leonid Chindelevitch
2021	J	`jnl`	Improved Recovery Guarantees and Sampling Strategies for TV Minimization in Compressive Imaging. SIAM J. Imaging Sci. Ben Adcock, Nick C. Dexter, Qinghong Xu
2021	—	`conf`	Learning High-Dimensional Hilbert-Valued Functions With Deep Neural Networks From Limited Data. AAAI Spring Symposium: MLPS Ben Adcock, Simone Brugiapaglia, Nick C. Dexter, Sebastian Moraga
2021	J	`jnl`	The Gap between Theory and Practice in Function Approximation with Deep Neural Networks. SIAM J. Math. Data Sci. Ben Adcock, Nick C. Dexter
2020	C	`conf`	An Interpretable Classification Method for Predicting Drug Resistance in M. Tuberculosis. WABI Hooman Zabeti, Nick C. Dexter, Amir Hosein Safari, Nafiseh Sedaghat, Maxwell W. Libbrecht, Leonid Chindelevitch
2020	J	`jnl`	Deep Neural Networks Are Effective At Learning High-Dimensional Hilbert-Valued Functions From Limited Data. CoRR Ben Adcock, Simone Brugiapaglia, Nick C. Dexter, Sebastian Moraga
2020	J	`jnl`	Improved recovery guarantees and sampling strategies for TV minimization in compressive imaging. CoRR Ben Adcock, Nick C. Dexter, Qinghong Xu
2020	J	`jnl`	The gap between theory and practice in function approximation with deep neural networks. CoRR Ben Adcock, Nick C. Dexter
2018	J	`jnl`	Polynomial approximation via compressed sensing of high-dimensional functions on lower sets. Math. Comput. Abdellah Chkifa, Nick C. Dexter, Hoang Tran, Clayton G. Webster
2016	J	`jnl`	Explicit cost bounds of stochastic Galerkin approximations for parameterized PDEs with random coefficients. Comput. Math. Appl. Nick C. Dexter, Clayton G. Webster, Guannan Zhang