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GRINN: A Physics-Informed Neural Network for solving hydrodynamic
  systems in the presence of self-gravity

GRINN: A Physics-Informed Neural Network for solving hydrodynamic systems in the presence of self-gravity

15 August 2023
Sayantan Auddy
Ramit Dey
N. Turner
S. Basu
    PINNAI4CE
ArXiv (abs)PDFHTMLGithub

Papers citing "GRINN: A Physics-Informed Neural Network for solving hydrodynamic systems in the presence of self-gravity"

4 / 4 papers shown
APRIL: Auxiliary Physically-Redundant Information in Loss - A physics-informed framework for parameter estimation with a gravitational-wave case study
APRIL: Auxiliary Physically-Redundant Information in Loss - A physics-informed framework for parameter estimation with a gravitational-wave case study
Matteo Scialpi
Francesco Di Clemente
Leigh Smith
Michał Bejger
145
0
0
15 Oct 2025
Neural Networks as Surrogate Solvers for Time-Dependent Accretion Disk Dynamics
Neural Networks as Surrogate Solvers for Time-Dependent Accretion Disk DynamicsAstrophysical Journal Letters (ApJL), 2025
S. Mao
Weiqi Wang
Sifan Wang
R. Dong
Lu Lu
K. M. Yi
P. Perdikaris
Andrea Isella
Sébastien Fabbro
Lile Wang
PINNAI4CE
203
0
0
24 Sep 2025
Unraveling particle dark matter with Physics-Informed Neural Networks
Unraveling particle dark matter with Physics-Informed Neural NetworksPhysics Letters B (Phys. Lett. B), 2025
M.P. Bento
H.B. Câmara
J.F. Seabra
442
4
0
24 Feb 2025
ASURA-FDPS-ML: Star-by-star Galaxy Simulations Accelerated by Surrogate Modeling for Supernova Feedback
ASURA-FDPS-ML: Star-by-star Galaxy Simulations Accelerated by Surrogate Modeling for Supernova FeedbackAstrophysical Journal (ApJ), 2024
Keiya Hirashima
K. Moriwaki
M. Fujii
Y. Hirai
T. Saitoh
Junnichiro Makino
Ulrich P. Steinwandel
Shirley Ho
254
3
0
30 Oct 2024
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