A data driven approach to classify descriptors based on their efficiency in translating noisy trajectories into physically-relevant information

Reconstructing the physical complexity of many-body dynamical systems can be a hard task. Starting from the trajectories of their constitutive units (raw data), typical approaches require choosing adequate parameters/descriptors to convert them into time-series that are then analyzed to extract huma...

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Bibliografski detalji

Glavni autori:	Simone Martino, Domiziano Doria, Chiara Lionello, Matteo Becchi, Giovanni M Pavan
Format:	Artigo
Jezik:	Inglês
Izdano:	IOP Publishing 2025-01-01
Serija:	Machine Learning: Science and Technology
Teme:	high-dimensional analysis dimensionality reduction information extraction time-series analysis unsupervised clustering descriptors
Online pristup:	https://doi.org/10.1088/2632-2153/adfa66
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