论文标题
Montecarlomeasurements.jl：通过方法超载的任意多元分布的非线性传播
MonteCarloMeasurements.jl: Nonlinear Propagation of Arbitrary Multivariate Distributions by means of Method Overloading
论文作者
论文摘要
该手稿概述了一个软件包，该软件包通过蒙特卡洛方法促进使用概率分布的工作，以允许通过任意函数传播多元概率分布的方式。我们提供了一个\ emph {type}，该\ emph {type}代表未加权样本的内部向量，即\ texttt {newerles}，它是\ texttt {real}数字的子类型，并且通过方法中载来计算中的定期实际数字，并且行为就像定期的实数。这使该软件易于使用，并给用户提供最小的摩擦。我们强调了这种设计如何促进SIMD指令的最佳用法，并通过现成的ode求解器以及具有自动差异化的稳健概率优化来展示不确定性传播的软件包。
This manuscript outlines a software package that facilitates working with probability distributions by means of Monte-Carlo methods, in a way that allows for propagation of multivariate probability distributions through arbitrary functions. We provide a \emph{type} that represents probability distributions by an internal vector of unweighted samples, \texttt{Particles}, which is a subtype of a \texttt{Real} number and behaves just like a regular real number in calculations by means of method overloading. This makes the software easy to work with and presents minimal friction for the user. We highlight how this design facilitates optimal usage of SIMD instructions and showcase the package for uncertainty propagation through an off-the-shelf ODE solver, as well as for robust probabilistic optimization with automatic differentiation.
