Deep Ray

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Assad OberaiAME, USCDirección de correo verificada de usc.edu
Jan S HesthavenProfessor of Mathematics and Provost, Ecole Polytechnique Federale de Lausanne (EPFL)Dirección de correo verificada de epfl.ch
Dhruv PatelPostdoctoral fellow, StanfordDirección de correo verificada de stanford.edu
Siddhartha MishraProfessor of Applied Mathematics, ETH Zurich, SwitzerlandDirección de correo verificada de sam.math.ethz.ch
Praveen ChandrashekarCenter for Applicable Mathematics, Tata Institute of Fundamental ResearchDirección de correo verificada de tifrbng.res.in
Kjetil Olsen LyeSINTEFDirección de correo verificada de sintef.no
Christian RohdeUniversität StuttgartDirección de correo verificada de mathematik.uni-stuttgart.de
Qian WangBeijing Computational Science Research Center, EPFL, Tsinghua UniversityDirección de correo verificada de csrc.ac.cn
Ulrik Skre FjordholmUniversity of OsloDirección de correo verificada de math.uio.no
Jim MagieraIANS, University of StuttgartDirección de correo verificada de mathematik.uni-stuttgart.de
Harisankar RamaswamyPhD student , University of Southern CaliforniaDirección de correo verificada de usc.edu
Beatrice RiviereNoah G. Harding Chair and Prof. of Computational Applied Mathematics and Operations Research at RiceDirección de correo verificada de rice.edu
Chen LiuDepartment of Mathematical Sciences, University of ArkansasDirección de correo verificada de uark.edu
Ujjwal KoleyAssociate Professor, TIFR-Centre for Applicable Mathematics, BangaloreDirección de correo verificada de math.tifrbng.res.in
Tanmay SarkarAssistant professor in IIT JammuDirección de correo verificada de iitjammu.ac.in
Christopher ThieleGraduate Student, Rice UniversityDirección de correo verificada de rice.edu
Tim De RyckETH ZürichDirección de correo verificada de math.ethz.ch
Saeed MoazamiUniversity of Southern California (USC)Dirección de correo verificada de usc.edu

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Deep Ray

Assistant Professor, University of Maryland

Dirección de correo verificada de umd.edu - Página principal

Deep Learning Conservation laws Uncertainty quantification CFD Pore-scale dynamics


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Non-intrusive reduced order modeling of unsteady flows using artificial neural networks with application to a combustion problem Q Wang, JS Hesthaven, D Ray Journal of computational physics 384, 289-307, 2019	284	2019
Deep learning observables in computational fluid dynamics KO Lye, S Mishra, D Ray Journal of Computational Physics 410, 109339, 2020	182	2020
An artificial neural network as a troubled-cell indicator D Ray, JS Hesthaven Submitted, 2017	181	2017
Controlling oscillations in high-order discontinuous Galerkin schemes using artificial viscosity tuned by neural networks N Discacciati, JS Hesthaven, D Ray Journal of Computational Physics 409, 109304, 2020	90	2020
Constraint-aware neural networks for Riemann problems J Magiera, D Ray, JS Hesthaven, C Rohde Journal of Computational Physics 409, 109345, 2020	78	2020
Detecting troubled-cells on two-dimensional unstructured grids using a neural network D Ray, JS Hesthaven Journal of Computational Physics 397, 108845, 2019	78	2019
Iterative surrogate model optimization (ISMO): An active learning algorithm for PDE constrained optimization with deep neural networks KO Lye, S Mishra, D Ray, P Chandrashekar Computer Methods in Applied Mechanics and Engineering 374, 113575, 2021	77	2021
Entropy stable scheme on two-dimensional unstructured grids for Euler equations D Ray, P Chandrashekar, US Fjordholm, S Mishra Communications in Computational Physics 19 (5), 1111-1140, 2016	64	2016
Solution of physics-based Bayesian inverse problems with deep generative priors DV Patel, D Ray, AA Oberai Computer Methods in Applied Mechanics and Engineering 400, 115428, 2022	49	2022
Controlling oscillations in spectral methods by local artificial viscosity governed by neural networks L Schwander, D Ray, JS Hesthaven Journal of Computational Physics 431, 110144, 2021	36	2021
Variationally mimetic operator networks D Patel, D Ray, MRA Abdelmalik, TJR Hughes, AA Oberai Computer Methods in Applied Mechanics and Engineering 419, 116536, 2024	32	2024
A sign preserving WENO reconstruction method US Fjordholm, D Ray Journal of Scientific Computing 68, 42-63, 2016	30	2016
The efficacy and generalizability of conditional GANs for posterior inference in physics-based inverse problems D Ray, H Ramaswamy, DV Patel, AA Oberai arXiv preprint arXiv:2202.07773, 2022	24	2022
An entropy stable finite volume scheme for the two dimensional Navier–Stokes equations on triangular grids D Ray, P Chandrashekar Applied Mathematics and Computation 314, 257-286, 2017	20	2017
Multilevel Monte Carlo finite difference methods for fractional conservation laws with random data U Koley, D Ray, T Sarkar SIAM/ASA Journal on Uncertainty Quantification 9 (1), 65-105, 2021	18	2021
A pressure-correction and bound-preserving discretization of the phase-field method for variable density two-phase flows C Liu, D Ray, C Thiele, L Lin, B Riviere Journal of Computational Physics 449, 110769, 2022	15	2022
Entropy stable schemes for compressible Euler equations D Ray, P Chandrashekar Int. J. Numer. Anal. Model. Ser. B 4 (4), 335-352, 2013	15	2013
Solution of physics-based inverse problems using conditional generative adversarial networks with full gradient penalty D Ray, J Murgoitio-Esandi, A Dasgupta, AA Oberai Computer Methods in Applied Mechanics and Engineering 417, 116338, 2023	14	2023
A dimension-reduced variational approach for solving physics-based inverse problems using generative adversarial network priors and normalizing flows A Dasgupta, DV Patel, D Ray, EA Johnson, AA Oberai Computer Methods in Applied Mechanics and Engineering 420, 116682, 2024	10	2024
On the approximation of rough functions with deep neural networks T De Ryck, S Mishra, D Ray SeMA Journal 79 (3), 399-440, 2022	10	2022

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