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probabilistic models

Differentiating ensembles and sample spaces: Alignment between statistical mechanics and probability theory

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Preamble Sample space is the primary concept introduced in any probability and statistics books and in papers. However, there needs to be more clarity about what constitutes a sample space in general: there is no explicit distinction between the unique event set and the replica sets. The...

Bayesian rabbit holes: Decoding conditional probability with non-commutative algebra

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Preamble    The White Rabbit (Wikipedia)A novice analyst or even experienced (data) scientist would have thought that the bar notation $|$ in representing conditional probability carries some different operational mathematics. Primarily when written in explicit distribution functions $p(x|y)$....

A New Matrix Mathematics for Deep Learning : Random Matrix Theory of Deep Learning

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Preamble     Figure: Definition of Randomness (Compagner 1991, Delft University)Development of deep learning systems (DLs)  increased our hopes to develop more autonomous systems. Based on the hierarchal learning of representations, deep learning defies the basic learning theory that beg the...