Statistical field theory for neural ...
Helias, Moritz.

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  • Statistical field theory for neural networks
  • 紀錄類型: 書目-電子資源 : Monograph/item
    正題名/作者: Statistical field theory for neural networks/ by Moritz Helias, David Dahmen.
    作者: Helias, Moritz.
    其他作者: Dahmen, David.
    出版者: Cham :Springer International Publishing : : 2020.,
    面頁冊數: xvii, 203 p. :ill., digital ;24 cm.
    內容註: Introduction -- Probabilities, moments, cumulants -- Gaussian distribution and Wick's theorem -- Perturbation expansion -- Linked cluster theorem -- Functional preliminaries -- Functional formulation of stochastic differential equations -- Ornstein-Uhlenbeck process: The free Gaussian theory -- Perturbation theory for stochastic differential equations -- Dynamic mean-field theory for random networks -- Vertex generating function -- Application: TAP approximation -- Expansion of cumulants into tree diagrams of vertex functions -- Loopwise expansion of the effective action - Tree level -- Loopwise expansion in the MSRDJ formalism -- Nomenclature.
    Contained By: Springer Nature eBook
    標題: Stochastic differential equations. -
    電子資源: https://doi.org/10.1007/978-3-030-46444-8
    ISBN: 9783030464448
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