65 citations · 111 across the 12 of their papers we have counts for
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physics.ao-ph2022★ 4 cited
Spatio-Temporal Super-Resolution Data Assimilation (SRDA) Utilizing Deep Neural Networks with Domain Generalization
Yuki Yasuda, Ryo Onishi
Deep learning has recently gained attention in the atmospheric and oceanic sciences for its potential to improve the accuracy of numerical simulations or to reduce computational co…
physics.flu-dyn2022
Rotationally Equivariant Super-Resolution of Velocity Fields in Two-Dimensional Fluids Using Convolutional Neural Networks
Yuki Yasuda, Ryo Onishi
This paper investigates the super-resolution (SR) of velocity fields in two-dimensional fluids from the viewpoint of rotational equivariance. SR refers to techniques that estimate…