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Comparative Analysis of Predicting Subsequent Steps in Hénon Map
This paper explores the prediction of subsequent steps in H\'enon Map using various machine learning techniques.
Identifying regions of importance in wall-bounded turbulence through explainable deep learning
One of the key strategies has been to study interactions among the energy-containing coherent structures in the flow.
Using Machine Learning to predict extreme events in the Hénon map
Machine Learning (ML) inspired algorithms provide a flexible set of tools for analyzing and forecasting chaotic dynamical systems.
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