Pushing Mathematical Limits, a Neural Network Learns Fluid Flow

Dana Mackenzie

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PDF(597 KB)
Engineering ›› 2021, Vol. 7 ›› Issue (5) : 550-551. DOI: 10.1016/j.eng.2021.03.009

Pushing Mathematical Limits, a Neural Network Learns Fluid Flow

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Dana Mackenzie. Pushing Mathematical Limits, a Neural Network Learns Fluid Flow. Engineering, 2021, 7(5): 550‒551 https://doi.org/10.1016/j.eng.2021.03.009

References

[[1]]
Li Z, Kovachki N, Azizzadenesheli K, Liu B, Bhattacharya K, Stuart A, et al. Fourier neural operator for parametric partial differential equations. 2020. arXiv:2010.08895.
[[2]]
McCartney S. Eniac: the triumphs and tragedies of the world’s first computer. New York: Walker and Company; 1999.
[[3]]
Silver D, Schrittwieser J, Simonyan K, Antonoglou I, Huang A, Guez A, et al. Mastering the game of Go without human knowledge. Nature 2017;550:354–9.
[[4]]
Girshick R, Donahue J, Darrell T, Malik J. Rich feature hierarchies for accurate object detection and semantic segmentation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR); 2014 Jun 23– 28; Columbus, OH, USA; 2014. p. 580–7.
[[5]]
Stakgold I, Holst M. Green’s functions and boundary value problems. 3rd ed. Hoboken: Wiley Interscience; 2011.
[[6]]
Frisch U. Turbulence: the legacy of A. N. Kolmogorov. Cambridge: Cambridge University Press; 1995.
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