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Cited article:

Higher-order error estimates for physics-informed neural networks approximating the primitive equations

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Partial Differential Equations and Applications 4 (4) (2023)
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Numerical Simulations of the Two-Dimensional Inviscid Hydrostatic Primitive Equations with Humidity and Saturation

Arthur Bousquet, Youngjoon Hong, Roger Temam and Joseph Tribbia
Journal of Scientific Computing 83 (2) (2020)
https://doi.org/10.1007/s10915-020-01215-y

The nonlinear 2D supercritical inviscid shallow water equations in a rectangle

Aimin Huang, Madalina Petcu and Roger Temam
Asymptotic Analysis 93 (3) 187 (2015)
https://doi.org/10.3233/ASY-151293

Partial Differential Equations: Theory, Control and Approximation

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Partial Differential Equations: Theory, Control and Approximation 67 (2014)
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Goal-oriented a posteriori error estimation for finite volume methods

Qingshan Chen and Max Gunzburger
Journal of Computational and Applied Mathematics 265 69 (2014)
https://doi.org/10.1016/j.cam.2013.10.004

A higher order Finite Volume resolution method for a system related to the inviscid primitive equations in a complex domain

Arthur Bousquet, Gung-Min Gie, Youngjoon Hong and Jacques Laminie
Numerische Mathematik 128 (3) 431 (2014)
https://doi.org/10.1007/s00211-014-0622-4

Finite Volume Multilevel Approximation of the Shallow Water Equations

Arthur Bousquet, Martine Marion and Roger Temam
Chinese Annals of Mathematics, Series B 34 (1) 1 (2013)
https://doi.org/10.1007/s11401-012-0760-x

The Euler equations in planar nonsmooth convex domains

Claude Bardos, Francesco Di Plinio and Roger Temam
Journal of Mathematical Analysis and Applications 407 (1) 69 (2013)
https://doi.org/10.1016/j.jmaa.2013.05.005