Treffer: Fast Python sampler of the von Mises Fisher distribution ; Échantillonneur rapide de la distribution de von Mises Fisher en Python
Title:
Fast Python sampler of the von Mises Fisher distribution ; Échantillonneur rapide de la distribution de von Mises Fisher en Python
Authors:
Contributors:
Concurrency, Mobility and Transactions (COMETE), Laboratoire d'informatique de l'École polytechnique Palaiseau (LIX), École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS)-Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), École polytechnique (X)-Centre National de la Recherche Scientifique (CNRS), European Project: 835294,H2020 Pilier ERC,HYPATIA(2019)
Source:
https://hal.science/hal-04004568 ; 2023.
Publisher Information:
HAL CCSD
Publication Year:
2023
Collection:
Archive ouverte HAL (Hyper Article en Ligne, CCSD - Centre pour la Communication Scientifique Directe)
Subject Terms:
Document Type:
Report
report
Language:
English
Relation:
info:eu-repo/grantAgreement//835294/EU/Privacy and Utility Allied/HYPATIA; hal-04004568; https://hal.science/hal-04004568; https://hal.science/hal-04004568/document; https://hal.science/hal-04004568/file/main.pdf
Availability:
Rights:
http://hal.archives-ouvertes.fr/licences/publicDomain/ ; info:eu-repo/semantics/OpenAccess
Accession Number:
edsbas.8C991DF
Database:
BASE
Weitere Informationen
This paper implements a method for sampling from the d-dimensional Von Mises Fisher distribution using NumPy, focusing on speed and readability. The complexity of the algorithm is O(nd) for n samples, which is theoretically optimal taking into account that nd is the output size.