4 citations · 4 across the 2 of their papers we have counts for
2 papers
physics.flu-dyn2022★ 4 cited
Physics-Informed CNNs for Super-Resolution of Sparse Observations on Dynamical Systems
Daniel Kelshaw, Georgios Rigas, Luca Magri
In the absence of high-resolution samples, super-resolution of sparse observations on dynamical systems is a challenging problem with wide-reaching applications in experimental set…
physics.flu-dyn2022
Physics-Informed Convolutional Neural Networks for Corruption Removal on Dynamical Systems
Daniel Kelshaw, Luca Magri
Measurements on dynamical systems, experimental or otherwise, are often subjected to inaccuracies capable of introducing corruption; removal of which is a problem of fundamental im…