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The Past as a Stochastic Process

arXiv 2112.05876 ↗First posted 11 Dec 2021stat.AP cs.LG econ.EMcited by 0

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Abstract (arXiv)

Historical processes manifest remarkable diversity. Nevertheless, scholars have long attempted to identify patterns and categorize historical actors and influences with some success. A stochastic process framework provides a structured approach for the analysis of large historical datasets that allows for detection of sometimes surprising patterns, identification of relevant causal actors both endogenous and exogenous to the process, and comparison between different historical cases. The combination of data, analytical tools and the organizing theoretical framework of stochastic processes complements traditional narrative approaches in history and archaeology.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 111 references that are in the map. First posted on arXiv 11 Dec 2021.

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References · 3

  1. 2021Deeptime: a Python library for machine learning dynamical models from time series datacited by 38
  2. 2018Learning Stochastic Differential Equations With Gaussian Processes Without Gradient Matchingcited by 23
  3. 2017Individuals, Institutions, and Innovation in the Debates of the French Revolutioncited by 10

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