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Stochastic sampling of the hyperspherical von mises–fisher distribution without rejection methods | IEEE Conference Publication | IEEE Xplore

Stochastic sampling of the hyperspherical von mises–fisher distribution without rejection methods


Abstract:

We propose a novel sampling algorithm for the von Mises-Fisher distribution on the unit hypersphere. Unlike previous works, we show a solution for an arbitrary number of ...Show More

Abstract:

We propose a novel sampling algorithm for the von Mises-Fisher distribution on the unit hypersphere. Unlike previous works, we show a solution for an arbitrary number of dimensions without requiring rejection sampling. As a result, the proposed algorithm has a deterministic runtime. The key idea consists in applying the inversion method to a one-dimensional subproblem and analytically calculating the integral occurring in the distribution function. The proposed method is most efficient for odd numbers of dimensions. We compare the algorithm to a state-of-the-art rejection sampling method in simulations.
Date of Conference: 06-08 October 2015
Date Added to IEEE Xplore: 17 December 2015
ISBN Information:
Conference Location: Bonn, Germany

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