M. Morimoto, K. Fukami, R. Maulik, R. Vinuesa, and K. Fukagata, "Assessments of epistemic uncertainty using Gaussian stochastic weight averaging for fluid-flow regression," Physica D: Nonlinear Phenomena 440, 133454 (2022)
(preprint: arxiv:2109.08248 [physics.flu-dyn])
[Featured research in CFD35] M. Morimoto, K. Fukami, R. Maulik, R. Vinuesa, and K. Fukagata, Featured Research in CFD35: "Model-form uncertainty quantification in neural-network-based fluid-flow estimation," Nagare - Journal of Japan Society of Fluid Mechanics 41, 89-92 (2022).
M. Morimoto, K. Fukami, K. Zhang, and K. Fukagata, “Generalization techniques of neural networks for fluid flow estimation,” Neural Computing and Applications 34, 3647-3669 (2022).
(preprint: arXiv:2011.11911 [physics.flu-dyn])
[Sample code for Grad-CAM]
K. Fukami, K. Hasegawa, T. Nakamura, M. Morimoto, and K. Fukagata, "Model order reduction with neural networks: Application to laminar and turbulent flows," SN Computer Science 2, 467 (2021). (Open Access)
(preprint: arXiv:2011.10277 [physics.flu-dyn])
[Editor's Pick] M. Morimoto, K. Fukami, and K. Fukagata, "Experimental velocity data estimation for imperfect particle images using machine learning," Physics of Fluids 33, 087121 (2021).
(preprint: arXiv:2005.00756 [physics.flu-dyn])
[Sample code on GitHub]
M. Morimoto, K. Fukami, K. Zhang, A. G. Nair, and K. Fukagata, "Convolutional neural networks for fluid flow analysis: toward effective metamodeling and low dimensionalization," Theoretical and Computational Fluid Dynamics 35, 633-658 (2021).
(preprint: arxiv:2101.02535 [physics.flu-dyn])
[Sample code on GitHub]
[Featured research in CFD33] M. Morimoto, K. Fukami, K. Hasegawa, T. Murata, H. Murakami, and K. Fukagata, "Improvement of PIV by data augmentation based on machine learning," Nagare - Journal of Japan Society of Fluids Mechanics 39(2), pp.84-87 (2020).
N. Moriya, K. Fukami, Y. Nabae, M. Morimoto, T. Nakamura, and K. Fukagata, "Inserting machine-learned virtual wall velocity for large-eddy simulation of turbulent channel flows," arXiv:2106.09271 [physics.flu-dyn].
M. Matsuo, T. Nakamura, M. Morimoto, K. Fukami, K. Fukagata, "Supervised convolutional network for three-dimensional fluid data reconstruction from sectional flow fields with adaptive super-resolution assistance," arXiv:2103.09020 [physics.flu-dyn].