Assessments of model-form uncertainty using Gaussian stochastic weight averaging for fluid-flow regression. - Masaki Morimoto; Kai Fukami; Romit Maulik; Ricardo Vinuesa; Koji Fukagata (CoRR, 2021)

Global field reconstruction from sparse sensors with Voronoi tessellation-assisted deep learning. - Kai Fukami; Romit Maulik; Nesar Ramachandra; Koji Fukagata; Kunihiko Taira (Nat. Mach. Intell., 2021)

Model Order Reduction with Neural Networks: Application to Laminar and Turbulent Flows. - Kai Fukami; Kazuto Hasegawa; Taichi Nakamura; Masaki Morimoto; Koji Fukagata (SN Comput. Sci., 2021)

Applying Bayesian optimization with Gaussian process regression to computational fluid dynamics problems. - Yuki Morita; Saleh Rezaeiravesh; N. Tabatabaei; Ricardo Vinuesa; Koji Fukagata; Philipp Schlatter (J. Comput. Phys., 2022)

Generalization techniques of neural networks for fluid flow estimation. - Masaki Morimoto; Kai Fukami; Kai Zhang; Koji Fukagata (Neural Comput. Appl., 2022)

Towards quantum computing of turbulence. - Koji Fukagata (Nat. Comput. Sci., 2022)

Super-Resolution Analysis via Machine Learning: A Survey for Fluid Flows. - Kai Fukami; Koji Fukagata; Kunihiko Taira (CoRR, 2023)

Reconstructing Three-Dimensional Bluff Body Wake from Sectional Flow Fields with Convolutional Neural Networks. - Mitsuaki Matsuo; Kai Fukami; Taichi Nakamura; Masaki Morimoto; Koji Fukagata (SN Comput. Sci., 2024)