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1. (WO2018106964) CHARACTERISATION OF DYNAMICAL STATISTICAL SYSTEMS

Pub. No.:    WO/2018/106964    International Application No.:    PCT/US2017/065183
Publication Date: Fri Jun 15 01:59:59 CEST 2018 International Filing Date: Fri Dec 08 00:59:59 CET 2017
IPC: G06K 9/62
G06F 15/18
G06F 17/10
G06F 17/18
Applicants: NOBLE ARTIFICIAL INTELLIGENCE, INC.
Inventors: LEVY, Matthew Chase
Title: CHARACTERISATION OF DYNAMICAL STATISTICAL SYSTEMS
Abstract:
Machine learning is performed on input data representing a dynamical statistical system of entities having plural primary variables that vary time. A distribution function over time of the density of entities in a phase space, whose dimensions are the primary variables and secondary variables dependent on the rate of change of the primary variables, is derived and encoded as a sum of contour functions over time describing the contour in phase space of plural phaseons which are entities of a model of the dynamical statistical system that are localised in the phase space. Machine learning is performed on the encoded distribution function and/or at least one field in the effective configuration space whose dimensions are the primary variables, derived from the encoded distribution function. The encoding of the distribution function provides a representation which improves the performance of the machine learning techniques by simplifying hyperparameter optimisation.