Seguir
Akshay Subramaniam
Akshay Subramaniam
NVIDIA
Dirección de correo verificada de alumni.stanford.edu
Título
Citado por
Citado por
Año
NVIDIA SimNet™: An AI-accelerated multi-physics simulation framework
O Hennigh, S Narasimhan, MA Nabian, A Subramaniam, K Tangsali, ...
International conference on computational science, 447-461, 2021
3012021
Turbulence Enrichment using Physics-informed Generative Adversarial Networks
A Subramaniam, ML Wong, RD Borker, S Nimmagadda, SK Lele
arXiv preprint arXiv:2003.01907, 2020
622020
Fundamental properties of five Kepler stars using global asteroseismic quantities and ground-based observations
OL Creevey, G Doğan, A Frasca, AO Thygesen, S Basu, J Bhattacharya, ...
Astronomy & Astrophysics 537, A111, 2012
512012
A high-order weighted compact high resolution scheme with boundary closures for compressible turbulent flows with shocks
A Subramaniam, ML Wong, SK Lele
Journal of Computational Physics 397, 108822, 2019
352019
ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation
S Yu, W Hannah, L Peng, J Lin, MA Bhouri, R Gupta, B Lütjens, JC Will, ...
Advances in Neural Information Processing Systems 36, 22070-22084, 2023
282023
A unified high-order Eulerian method for continuum simulations of fluid flow and of elastic–plastic deformations in solids
NS Ghaisas, A Subramaniam, SK Lele
Journal of Computational Physics 371, 452-482, 2018
262018
High-order Eulerian simulations of multimaterial elastic–plastic flow
A Subramaniam, NS Ghaisas, SK Lele
Journal of Fluids Engineering 140 (5), 050904, 2018
262018
Max Rietmann, Jose del Aguila Ferrandis, Wonmin Byeon, Zhiwei Fang, and Sanjay Choudhry. Nvidia simnetˆ {TM}: an ai-accelerated multi-physics simulation framework
O Hennigh, S Narasimhan, MA Nabian, A Subramaniam, K Tangsali
arXiv preprint arXiv:2012.07938, 2020
222020
ClimSim: An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators
S Yu, WM Hannah, L Peng, MA Bhouri, R Gupta, J Lin, B Lütjens, JC Will, ...
NeurIPS, 2023
132023
High-order Eulerian methods for elastic-plastic flow in solids and coupling with fluid flows
NS Ghaisas, A Subramaniam, SK Lele
46th AIAA Fluid Dynamics Conference, 3350, 2016
132016
Man Long Wong, Raunak D Borker, Sravya Nimmagadda, and Sanjiva K Lele. Turbulence enrichment using physics-informed generative adversarial networks
A Subramaniam
arXiv preprint arXiv:2003.01907, 2020
112020
Computational Science—ICCS 2021
O Hennigh, S Narasimhan, MA Nabian, A Subramaniam, K Tangsali, ...
Springer, 2021
102021
PadeOps Github Repository
A Subramaniam, A Ghate, NS Ghaisas, MF Howland
See https://github. com/FPAL-Stanford-University/PadOps/tree/igridSGS (last …, 2021
102021
J. d. A. Ferrandis, W. Byeon, Z. Fang, and S. Choudhry,“Nvidia simnetˆ {TM}: an ai-accelerated multi-physics simulation framework,”
O Hennigh, S Narasimhan, MA Nabian, A Subramaniam, K Tangsali, ...
arXiv preprint arXiv:2012.07938 14, 2020
102020
Robust high-resolution simulations of compressible turbulent flows without filtering
H Song, AS Ghate, K Matsuno, J West, A Subramaniam, LJ Brown, ...
AIAA Aviation 2022 Forum, 4122, 2022
92022
Residual corrective diffusion modeling for km-scale atmospheric downscaling
M Mardani, N Brenowitz, Y Cohen, J Pathak, CY Chen, CC Liu, A Vahdat, ...
Communications Earth & Environment 6 (1), 124, 2025
82025
Simulations of shock induced interfacial instabilities including materials with strength
A Subramaniam
Stanford University, 2018
82018
Scalable parallel linear solver for compact banded systems on heterogeneous architectures
H Song, KV Matsuno, JR West, A Subramaniam, AS Ghate, SK Lele
Journal of Computational Physics 468, 111443, 2022
72022
Turbulence enrichment using physics-informed generative adversarial networks (2020)
A Subramaniam, ML Wong, RD Borker, S Nimmagadda, SK Lele
arXiv preprint arXiv:2003.01907, 2003
72003
Residual corrective diffusion modeling for km-scale atmospheric downscaling, 2024
M Mardani, N Brenowitz, Y Cohen, J Pathak, CY Chen, CC Liu, A Vahdat, ...
URL https://arxiv. org/abs/2309.15214, 2023
62023
El sistema no puede realizar la operación en estos momentos. Inténtalo de nuevo más tarde.
Artículos 1–20