Multidimensional variation for quasi-Monte Carlo

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Monte Carlo and Quasi-Monte Carlo Sampling (2009, background): “Functions with infinite variation are also often encountered in derivative pricing in finance [335].”
Estimates on the generalization error of physics-informed neural networks for approximating a class of inverse problems for PDEs (2020, background): “As long as the integrand h is of bounded Hardy-Krause variation [50], the error in (2.”
Generalized Hoeffding-Sobol Decomposition for Dependent Variables -Application to Sensitivity Analysis (2011, unknown): “The Monte Carlo algorithm was proposed by Sobol [36], and has been later improved by the Quasi Monte Carlo technique, performed by Owen [31].”
The sample size required in importance sampling (2015, methodology): “Owen and Zhou [50] combine Hesterberg’s idea with control variates to give an attractive, practical approach.”