Eric C. Cyr

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John N. ShadidSandia National Labs, Computational Mathematics Dept.; Univ. of New Mexico, Mathematics Dept.Patvirtintas el. paštas sandia.gov
Roger PawlowskiSandia National laboratoriesPatvirtintas el. paštas sandia.gov
Nathaniel TraskUniversity of PennsylvaniaPatvirtintas el. paštas seas.upenn.edu
Ravi G PatelScientist, Sandia National LabsPatvirtintas el. paštas sandia.gov
Raymond TuminaroSanida National LabsPatvirtintas el. paštas sandia.gov
Tim WildeySandia National LabsPatvirtintas el. paštas sandia.gov
Stephen BondResearch Scientist, Sandia National LaboratoriesPatvirtintas el. paštas sandia.gov
Mamikon GulianBooz Allen HamiltonPatvirtintas el. paštas bah.com
Paul LinLawrence Berkeley National LaboratoryPatvirtintas el. paštas lbl.gov
Luis ChaconLos Alamos National LaboratoryPatvirtintas el. paštas lanl.gov
Mitchell A. WoodSandia National LabsPatvirtintas el. paštas sandia.gov
Luke OlsonProfessor of Computer Science, University of Illinois at Urbana-ChampaignPatvirtintas el. paštas illinois.edu
Jacob B SchroderDept. of Math & Stats, University of New MexicoPatvirtintas el. paštas unm.edu
Stefanie GüntherResearcher at Lawrence Livermore National LaboratoryPatvirtintas el. paštas llnl.gov
Jehanzeb H ChaudhryUniversity of New MexicoPatvirtintas el. paštas unm.edu
Howard ElmanProfessor of Computer Science, University of MarylandPatvirtintas el. paštas umd.edu
Laura P. SwilerSandia National LaboratoriesPatvirtintas el. paštas sandia.gov
Sidafa CondeUniversity of Massachusetts DartmouthPatvirtintas el. paštas umassd.edu
James H AdlerTufts UniversityPatvirtintas el. paštas tufts.edu
Scott MacLachlanProfessor, Memorial University of NewfoundlandPatvirtintas el. paštas mun.ca

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Eric C. Cyr

Computational Mathematics Department, Sandia National Laboratories

Patvirtintas el. paštas sandia.gov - Pagrindinis puslapis

Computational Science Preconditioning Numerical PDEs Scientific Machine Learning


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
Thermodynamically consistent physics-informed neural networks for hyperbolic systems RG Patel, I Manickam, NA Trask, MA Wood, M Lee, I Tomas, EC Cyr Journal of Computational Physics 449, 110754, 2022	157	2022
Layer-parallel training of deep residual neural networks S Gunther, L Ruthotto, JB Schroder, EC Cyr, NR Gauger SIAM Journal on Mathematics of Data Science 2 (1), 1-23, 2020	125	2020
A physics-informed operator regression framework for extracting data-driven continuum models RG Patel, NA Trask, MA Wood, EC Cyr Computer Methods in Applied Mechanics and Engineering 373, 113500, 2021	118	2021
Robust training and initialization of deep neural networks: An adaptive basis viewpoint EC Cyr, MA Gulian, RG Patel, M Perego, NA Trask Mathematical and Scientific Machine Learning, 512-536, 2020	90	2020
Scalable implicit incompressible resistive MHD with stabilized FE and fully-coupled Newton–Krylov-AMG JN Shadid, RP Pawlowski, EC Cyr, RS Tuminaro, L Chacón, PD Weber Computer Methods in Applied Mechanics and Engineering 304, 1-25, 2016	85	2016
A new approximate block factorization preconditioner for two-dimensional incompressible (reduced) resistive MHD EC Cyr, JN Shadid, RS Tuminaro, RP Pawlowski, L Chacón SIAM Journal on Scientific Computing 35 (3), B701-B730, 2013	84	2013
Monolithic multigrid methods for two-dimensional resistive magnetohydrodynamics JH Adler, TR Benson, EC Cyr, SP MacLachlan, RS Tuminaro SIAM Journal on Scientific Computing 38 (1), B1-B24, 2016	58	2016
Block preconditioners for stable mixed nodal and edge finite element representations of incompressible resistive MHD EG Phillips, JN Shadid, EC Cyr, HC Elman, RP Pawlowski SIAM Journal on Scientific Computing 38 (6), B1009-B1031, 2016	51	2016
Stabilization and scalable block preconditioning for the Navier–Stokes equations EC Cyr, JN Shadid, RS Tuminaro Journal of Computational Physics 231 (2), 345-363, 2012	50	2012
A first‐order system least‐squares finite element method for the Poisson‐Boltzmann equation SD Bond, JH Chaudhry, EC Cyr, LN Olson Journal of computational chemistry 31 (8), 1625-1635, 2010	48	2010
Partition of unity networks: deep hp-approximation K Lee, NA Trask, RG Patel, MA Gulian, EC Cyr arXiv preprint arXiv:2101.11256, 2021	47	2021
A block preconditioner for an exact penalty formulation for stationary MHD EG Phillips, HC Elman, EC Cyr, JN Shadid, RP Pawlowski SIAM Journal on Scientific Computing 36 (6), B930-B951, 2014	45	2014
The surfpack software library for surrogate modeling of sparse irregularly spaced multidimensional data A Giunta, L Swiler, S Brown, M Eldred, M Richards, E Cyr 11th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, 7049, 2006	44	2006
Advancing fusion with machine learning research needs workshop report D Humphreys, A Kupresanin, MD Boyer, J Canik, CS Chang, EC Cyr, ... Journal of Fusion Energy 39, 123-155, 2020	43	2020
EMPIRE-PIC: a performance portable unstructured particle-in-cell code MT Bettencourt, DAS Brown, KL Cartwright, EC Cyr, CA Glusa, PT Lin, ... Communications in Computational Physics 30 (SAND-2021-2806J), 2021	38	2021
Towards efficient backward-in-time adjoint computations using data compression techniques EC Cyr, JN Shadid, T Wildey Computer Methods in Applied Mechanics and Engineering 288, 24-44, 2015	27	2015
Teko: A block preconditioning capability with concrete example applications in Navier--Stokes and MHD EC Cyr, JN Shadid, RS Tuminaro SIAM Journal on Scientific Computing 38 (5), S307-S331, 2016	26	2016
A new class of finite element variational multiscale turbulence models for incompressible magnetohydrodynamics D Sondak, JN Shadid, AA Oberai, RP Pawlowski, EC Cyr, TM Smith Journal of Computational Physics 295, 596-616, 2015	26	2015
IMEX and exact sequence discretization of the multi-fluid plasma model ST Miller, EC Cyr, JN Shadid, RMJ Kramer, EG Phillips, S Conde, ... Journal of Computational Physics 397, 108806, 2019	21	2019
Monolithic multigrid methods for magnetohydrodynamics JH Adler, TR Benson, EC Cyr, PE Farrell, SP MacLachlan, RS Tuminaro SIAM Journal on Scientific Computing 43 (5), S70-S91, 2021	20	2021

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