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Read more about Optimal transport between determinantal point processes and application to fast simulation.
Optimal transport between determinantal point processes and application to fast simulation#
The simulation of determinantal point processes by the classical algorithm introduced by Hough et al. suffer from two flaws : a large number of rejections and a huge number of computations to obtain the densities. For radially symmetric determinantal point processes, like the \(\beta\)-Ginibre or Bergman processes, we show how to overcome these two difficulties and obtain a fast approximate simulation. The errors are evaluated in Wasserstein distances and shown to be asymptotically evanescent. The code is freely available at https://gitlab.inria.fr/gmoro/point_process
Note
@article{decreusefond_moroz_2021,
author = {Laurent Decreusefond and Guillaume Moroz},
title = {Optimal transport between determinantal point processes and application to fast simulation},
journal = {Modern Stochastics: Theory and Applications},
volume = {8},
number = {2},
year = {2021},
pages = {209--237},
doi = {10.15559/21-VMSTA180},
issn = {2351-6046}}