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The bliss of dimensionality: how an unsupervised criterion identifies optimal low-resolution representations of high-dimensional datasets
Selecting the optimal resolution for discretizing high-dimensional data is a central problem in physics and data analysis, particularly in unsupervised settings where the underlying distribution is unknown. The Relevance-Resolution (Res-Rel) framework addresses this issue through an information-theo
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