Bayesian methods in Structural Equation Modeling (SEM) represent a paradigm shift in statistical analysis, integrating prior beliefs with empirical data to derive robust parameter estimates. This ...
The paper presents a Bayesian framework for the calibration of financial models using neural stochastic differential equations (neural SDEs), for which we also formulate a global universal ...
Deterministic simulation models are used to understand environmental processes and guide policy development by decision makers. In order to make informed decisions, uncertainty about input and output ...
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