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Renormalization group flow and other ideas inspired by physics for nonlinear filters, Bayesian decisions and transport

机译:重归一化群流和其他受物理学启发的思想,用于非线性滤波器,贝叶斯决策和传输

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摘要

We describe many new ideas for research in particle flow corresponding to Bayes' rule. Some of these ideas were inspired by quantum field theory and classical electromagnetism whereas others were taken from mathematics or signal processing. For example, we discuss renormalization group flow, Ricci flow, Yang-Mills equations, the Dirac approximation, Kronecker product expansions to estimate the covariance matrix, charge quantization, etc. Three new algorithms for particle flow inspired by renormalization group flow are derived in detail.
机译:我们描述了许多与贝叶斯定律相对应的研究新思想的思路。这些思想中的一些受量子场论和经典电磁学的启发,而另一些则取自数学或信号处理。例如,我们讨论了重归一化群流,Ricci流,Yang-Mills方程,狄拉克逼近,Kronecker乘积展开以估计协方差矩阵,电荷量化等。详细介绍了由重归一化群流启发的三种粒子流新算法。

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