Ethan N. Epperly
Ethan N. Epperly
PhD Candidate in Applied and Computational Math, Caltech
Verified email at - Homepage
Cited by
Cited by
A theory of quantum subspace diagonalization
EN Epperly, L Lin, Y Nakatsukasa
SIAM Journal on Matrix Analysis and Applications 43 (3), 1263-1290, 2022
Randomly pivoted Cholesky: Practical approximation of a kernel matrix with few entry evaluations
Y Chen, EN Epperly, JA Tropp, RJ Webber
arXiv preprint arXiv:2207.06503, 2022
Transient solute drag and strain aging of dislocations
EN Epperly, RB Sills
Acta Materialia 193, 182-190, 2020
XTrace: Making the Most of Every Sample in Stochastic Trace Estimation
EN Epperly, JA Tropp, RJ Webber
SIAM Journal on Matrix Analysis and Applications 45 (1), 1-23, 2024
Comparison of continuum and cross-core theories of dynamic strain aging
EN Epperly, RB Sills
Journal of the Mechanics and Physics of Solids 141, 103944, 2020
Efficient error and variance estimation for randomized matrix computations
EN Epperly, JA Tropp
SIAM Journal on Scientific Computing 46 (1), A508-A528, 2024
(Lᵣ, Lᵣ, 1)-Decompositions, sparse component analysis, and the blind separation of sums of exponentials
N Govindarajan, EN Epperly, L De Lathauwer
SIAM Journal on Matrix Analysis and Applications 43 (2), 912–938, 2022
Kernel quadrature with randomly pivoted Cholesky
EN Epperly, E Moreno
Advances in Neural Information Processing Systems 36, 65850–65868, 2023
Robust, randomized preconditioning for kernel ridge regression
M Díaz, EN Epperly, Z Frangella, JA Tropp, RJ Webber
arXiv preprint arXiv:2304.12465, 2023
Graph-induced rank structures and their representations
S Chandrasekaran, EN Epperly, N Govindarajan
arXiv preprint arXiv:1911.05858, 2019
Fast and forward stable randomized algorithms for linear least-squares problems
EN Epperly
arXiv preprint arXiv:2311.04362, 2023
Minimal rank completions for overlapping blocks
EN Epperly, N Govindarajan, S Chandrasekaran
Linear Algebra and its Applications 627, 185-198, 2021
Smoothers for Matrix-Free Algebraic Multigrid Preconditioning of High-Order Finite Elements
EN Epperly, AT Barker, RD Falgout
Lawrence Livermore National Lab.(LLNL), Livermore, CA (United States …, 2020
The ESPRIT algorithm under high noise: Optimal error scaling and noisy super-resolution
Z Ding, EN Epperly, L Lin, R Zhang
arXiv preprint arXiv:2404.03885, 2024
Understanding H isotope adsorption and absorption of Al-alloys using modeling and experiments (LDRD:# 165724)
DK Ward, X Zhou, RA Karnesky, R Kolasinski, ME Foster, K Thurmer, ...
Sandia National Lab.(SNL-CA), Livermore, CA (United States), 2015
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