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The Importance of Architecture Choice in Deep Learning for Climate
  Applications

The Importance of Architecture Choice in Deep Learning for Climate Applications

21 February 2024
Simon Dräger
Maike Sonnewald
    AI4CE
ArXivPDFHTML

Papers citing "The Importance of Architecture Choice in Deep Learning for Climate Applications"

4 / 4 papers shown
Title
Southern Ocean Dynamics Under Climate Change: New Knowledge Through
  Physics-Guided Machine Learning
Southern Ocean Dynamics Under Climate Change: New Knowledge Through Physics-Guided Machine Learning
William Yik
Maike Sonnewald
Mariana C. A. Clare
Redouane Lguensat
AI4Cl
AI4CE
22
4
0
21 Oct 2023
Bridging observation, theory and numerical simulation of the ocean using
  Machine Learning
Bridging observation, theory and numerical simulation of the ocean using Machine Learning
Maike Sonnewald
Redouane Lguensat
Daniel C. Jones
P. Dueben
J. Brajard
Venkatramani Balaji
AI4Cl
AI4CE
38
99
0
26 Apr 2021
Bayesian neural networks for weak solution of PDEs with uncertainty
  quantification
Bayesian neural networks for weak solution of PDEs with uncertainty quantification
Xiaoxuan Zhang
K. Garikipati
AI4CE
29
11
0
13 Jan 2021
Fourier Neural Operator for Parametric Partial Differential Equations
Fourier Neural Operator for Parametric Partial Differential Equations
Zong-Yi Li
Nikola B. Kovachki
Kamyar Azizzadenesheli
Burigede Liu
K. Bhattacharya
Andrew M. Stuart
Anima Anandkumar
AI4CE
203
2,272
0
18 Oct 2020
1