The following includes all the MATLAB scripts necessary for implementing the algorithm described in the attached paper.
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Updated
Nov 13, 2023 - MATLAB
The following includes all the MATLAB scripts necessary for implementing the algorithm described in the attached paper.
Fast Generation of von Mises-Fisher Distributed Pseudo-Random Vectors
Directional Co-clustering with a Conscience (DCC)
Fit and manipulate a few probability distribution functions on the unit S2 sphere.
Spherical statistics in Python
This is the repository for the research project about the Generalized Procrustes Analysis using spatial anatomical information in fMRI data, i.e., the ProMises (Procrustes von Mises-Fisher) model
Sampling from the von Mises - Fisher distribution
Kernel density estimation on a sphere
Code for EMNLP18 paper "Spherical Latent Spaces for Stable Variational Autoencoders"
Tensorflow implementation of Hyperspherical Variational Auto-Encoders
Clustering routines for the unit sphere
Pytorch implementation of Hyperspherical Variational Auto-Encoders
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