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The Statistical Physics of Data Assimilation and Machine Learning (Hardcover, New Ed)
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The Statistical Physics of Data Assimilation and Machine Learning (Hardcover, New Ed)
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Data assimilation is a hugely important mathematical technique,
relevant in fields as diverse as geophysics, data science, and
neuroscience. This modern book provides an authoritative treatment
of the field as it relates to several scientific disciplines, with
a particular emphasis on recent developments from machine learning
and its role in the optimisation of data assimilation. Underlying
theory from statistical physics, such as path integrals and Monte
Carlo methods, are developed in the text as a basis for data
assimilation, and the author then explores examples from current
multidisciplinary research such as the modelling of shallow water
systems, ocean dynamics, and neuronal dynamics in the avian brain.
The theory of data assimilation and machine learning is introduced
in an accessible and unified manner, and the book is suitable for
undergraduate and graduate students from science and engineering
without specialized experience of statistical physics.
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