most citedPhysics-agnostic and Physics-infused machine learning for thin films flows: modeling, and predictions from small data

12 citations · 13 across the 3 of their papers we have counts for

collaborators
Showing math.DSShow all

1 paper · 1 filter

math.DS2023

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…