15 citations · 33 across the 8 of their papers we have counts for
3 papers · 1 filter
Maximum Information Extraction Via Clustering and Minimization of Shannon Entropy
Matteo Becchi, Giovanni Maria Pavan
In the analysis of any type of system, granting maximum information extraction from its data is non-trivial. Confidence in successful information extraction typically builds on pri…
Data-driven assessment of optimal spatiotemporal resolutions for information extraction in noisy time series data
Domiziano Doria, Simone Martino, Matteo Becchi +1
In general, comprehension of any type of complex system depends on the resolution used to examine the phenomena occurring within it. However, identifying a priori, for example, the…
"Layer-by-layer" Unsupervised Clustering of Statistically Relevant Fluctuations in Noisy Time-series Data of Complex Dynamical Systems
Matteo Becchi, Federico Fantolino, Giovanni M. Pavan
Complex systems are typically characterized by intricate internal dynamics that are often hard to elucidate. Ideally, this requires methods that allow to detect and classify in uns…