most citedReconstructing unsteady flows from sparse, noisy measurements with a physics-constrained convolutional neural network

11 citations · 23 across the 3 of their papers we have counts for

collaborators

3 papers

physics.flu-dyn2025★ 1 cited

Reconstruction of three-dimensional turbulent flows from sparse and noisy planar measurements: A weight-sharing neural network approach

Yaxin Mo, Luca Magri

This paper proposes a method for reconstructing three-dimensional turbulent flows from sparse measurements without the need for ground truth data during training. A weight-sharing…

physics.flu-dyn2024★ 11 cited

Reconstructing unsteady flows from sparse, noisy measurements with a physics-constrained convolutional neural network

Yaxin Mo, Luca Magri

Data from fluid flow measurements are typically sparse, noisy, and heterogeneous, often from mixed pressure and velocity measurements, resulting in incomplete datasets. In this pap…

cs.LG2024★ 11 cited

Decoder Decomposition for the Analysis of the Latent Space of Nonlinear Autoencoders With Wind-Tunnel Experimental Data

Yaxin Mo, Tullio Traverso, Luca Magri

Turbulent flows are chaotic and multi-scale dynamical systems, which have large numbers of degrees of freedom. Turbulent flows, however, can be modelled with a smaller number of de…