3 citations · 5 across the 2 of their papers we have counts for
2 papers
physics.flu-dyn2021★ 2 cited
Parameterization of Forced Isotropic Turbulent Flow using Autoencoders and Generative Adversarial Networks
Kanishk, Tanishk Nandal, Prince Tyagi +1
Autoencoders and generative neural network models have recently gained popularity in fluid mechanics due to their spontaneity and low processing time instead of high fidelity CFD s…
physics.flu-dyn2021★ 3 cited
A comparative study of various Deep Learning techniques for spatio-temporal Super-Resolution reconstruction of Forced Isotropic Turbulent flows
T. S. Sachin Venkatesh, Rajat Srivastava, Pratyush Bhatt +2
Super-resolution is an innovative technique that upscales the resolution of an image or a video and thus enables us to reconstruct high-fidelity images from low-resolution data. Th…