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2004.10652
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A Fortran-Keras Deep Learning Bridge for Scientific Computing
Scientific Programming (SP), 2020
14 April 2020
J. Ott
M. Pritchard
Natalie Best
Erik J. Linstead
M. Curcic
Pierre Baldi
AI4CE
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Papers citing
"A Fortran-Keras Deep Learning Bridge for Scientific Computing"
23 / 23 papers shown
Title
Stabilizing PDE--ML coupled systems
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Online Test of a Neural Network Deep Convection Parameterization in ARP-GEM1
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Proof-of-concept: Using ChatGPT to Translate and Modernize an Earth System Model from Fortran to Python/JAX
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108
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13 Feb 2024
Multi-fidelity climate model parameterization for better generalization and extrapolation
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160
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19 Sep 2023
RoseNNa: A performant, portable library for neural network inference with application to computational fluid dynamics
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30 Jul 2023
In Situ Framework for Coupling Simulation and Machine Learning with Application to CFD
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John A. Evans
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88
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22 Jun 2023
Towards Exascale CFD Simulations Using the Discontinuous Galerkin Solver FLEXI
Marcel P. Blind
Min Gao
Daniel Kempf
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A. Schwarz
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102
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22 Jun 2023
Perspectives on AI Architectures and Co-design for Earth System Predictability
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M. Mudunuru
James A. Ang
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Simon D. Hammond
Maya Gokhale
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Philip W. Jones
65
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07 Apr 2023
Online model error correction with neural networks in the incremental 4D-Var framework
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A. Farchi
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Marc Bocquet
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Massimo Bonavita
172
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25 Oct 2022
Hard-Constrained Deep Learning for Climate Downscaling
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P. Harder
Alex Hernandez-Garcia
Venkatesh Ramesh
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08 Aug 2022
Deep Reinforcement Learning for Computational Fluid Dynamics on HPC Systems
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Marius Kurz
Philipp Offenhäuser
Dominic Viola
Oleksandr Shcherbakov
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Andrea Beck
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144
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13 May 2022
Productive Performance Engineering for Weather and Climate Modeling with Python
International Conference for High Performance Computing, Networking, Storage and Analysis (SC), 2022
Tal Ben-Nun
Linus Groner
Florian Deconinck
Tobias Wicky
Eddie Davis
...
Lukas Trumper
E. Wu
O. Fuhrer
T. Schulthess
Torsten Hoefler
115
21
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09 May 2022
Deep Learning Based Cloud Cover Parameterization for ICON
Journal of Advances in Modeling Earth Systems (JAMES), 2021
Arthur Grundner
Tom Beucler
Pierre Gentine
Fernando Iglesias‐Suarez
M. Giorgetta
Veronika Eyring
144
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21 Dec 2021
Climate-Invariant Machine Learning
Tom Beucler
Pierre Gentine
J. Yuval
Ankitesh Gupta
Liran Peng
...
F. Ahmed
P. O’Gorman
J. Neelin
N. Lutsko
Michael S. Pritchard
OOD
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208
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14 Dec 2021
Bridging observation, theory and numerical simulation of the ocean using Machine Learning
Environmental Research Letters (ERL), 2021
Maike Sonnewald
Redouane Lguensat
Daniel C. Jones
P. Dueben
J. Brajard
Venkatramani Balaji
AI4Cl
AI4CE
177
115
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26 Apr 2021
Using Machine Learning at Scale in HPC Simulations with SmartSim: An Application to Ocean Climate Modeling
Sam Partee
M. Ellis
Alessandro Rigazzi
S. Bachman
Gustavo M. Marques
Andrew Shao
Benjamin Robbins
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89
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13 Apr 2021
PythonFOAM: In-situ data analyses with OpenFOAM and Python
Journal of Computer Science (JCS), 2021
R. Maulik
Dimitrios K. Fytanidis
Bethany Lusch
V. Vishwanath
Saumil Patel
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91
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17 Mar 2021
Deploying deep learning in OpenFOAM with TensorFlow
R. Maulik
Himanshu Sharma
Saumil Patel
Bethany Lusch
Elise Jennings
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117
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01 Dec 2020
A Perspective on Machine Learning Methods in Turbulence Modelling
Andrea Beck
Marius Kurz
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148
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23 Oct 2020
Combining data assimilation and machine learning to infer unresolved scale parametrisation
J. Brajard
A. Carrassi
Marc Bocquet
Laurent Bertino
233
130
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09 Sep 2020
WeatherBench: A benchmark dataset for data-driven weather forecasting
Journal of Advances in Modeling Earth Systems (JAMES), 2020
S. Rasp
P. Dueben
S. Scher
Jonathan A. Weyn
Soukayna Mouatadid
Nils Thuerey
AI4Cl
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378
542
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02 Feb 2020
Using Machine Learning for Model Physics: an Overview
V. Krasnopolsky
Aleksei A. Belochitski
PINN
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151
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02 Feb 2020
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