We study the applicability of tools developed by the computer vision community for feature
learning and semantic image inpainting to perform data reconstruction of fluid turbulence …

Data reconstruction of rotating turbulent snapshots is investigated utilizing data-driven tools.
This problem is crucial for numerous geophysical applications and fundamental aspects …

We address the problem of data augmentation in a rotating turbulence set-up, a
paradigmatic challenge in geophysical applications. The goal is to reconstruct information in …

Inference problems for two-dimensional snapshots of rotating turbulent flows are studied.
We perform a systematic quantitative benchmark of point-wise and statistical reconstruction …

The problem of classifying turbulent environments from partial observation is key for some
theoretical and applied fields, from engineering to earth observation and astrophysics, eg, to …

We present TURB-Lagr, a new open database of 3d turbulent Lagrangian trajectories,
obtained by Direct Numerical Simulations (DNS) of the original Navier-Stokes equations in …

Gappy POD 是一种基于本征正交分解(proper orthogonal decomposition, POD)
的数据重构方法. 本文研究了gappy POD 在湍流数据重构中的应用, 主要关注了以下两个因素的 …

Gappy POD is a method of data reconstruction based on the proper orthogonal
decomposition (POD). We study the applicability of gappy POD to the reconstruction of fluid …

We present TURB-Hel, a database formed by two datasets of incompressible homogeneous
and isotropic turbulence, maintained in a statistically stationary state by fully helical forcing …

Dynamical systems are generally modeled using Partial Differential Equations (PDE). These
models are intricately linked to the way scientists observe the world and, as such, they are …