13 citations · 33 across the 10 of their papers we have counts for
3 papers · 1 filter
Nonlinear dimensionality reduction then and now: AIMs for dissipative PDEs in the ML era
Eleni D. Koronaki, Nikolaos Evangelou, Cristina P. Martin-Linares +2
This study presents a collection of purely data-driven workflows for constructing reduced-order models (ROMs) for distributed dynamical systems. The ROMs we focus on, are data-assi…
Physics-agnostic and Physics-infused machine learning for thin films flows: modeling, and predictions from small data
Cristina P. Martin-Linares, Yorgos M. Psarellis, Georgios Karapetsas +2
Numerical simulations of multiphase flows are crucial in numerous engineering applications, but are often limited by the computationally demanding solution of the Navier-Stokes (NS…
From partial data to out-of-sample parameter and observation estimation with Diffusion Maps and Geometric Harmonics
Eleni D. Koronaki, Nikolaos Evangelou, Yorgos M. Psarellis +2
A data-driven framework is presented, that enables the prediction of quantities, either observations or parameters, given sufficient partial data. The framework is illustrated via…