Implementation of the Expectation Maximization Algorithm for Hidden Markov Models including several Directional Distributions
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Updated
Apr 28, 2018 - Python
Implementation of the Expectation Maximization Algorithm for Hidden Markov Models including several Directional Distributions
A set of Course projects developed during the MSc on Mathematical Modelling and Computation at DTU
A directional-linear finite mixture model for clustering
Directional Co-clustering with a Conscience (DCC)
Uniformization tool for directional statistics on sphere
Spherical statistics in Python
A companion repository for 'Inverse Bayesian Optimization: Learning Human Acquisition Functions in an Exploration vs Exploitation Search Task'
Bingham Distribution Directional Statistics Library in Eigen3 / C++17
A curated BibTeX file with more than 1700 contributions in Directional Statistics
Hidden Markov Models with Directional Distributions for EEG data modeling
PCA on the torus using density ridges. Software companion for "Toroidal PCA via density ridges"
Tests for rotational symmetry on the hypersphere. Software companion for "On optimal tests for rotational symmetry against new classes of hyperspherical distributions"
Clustering routines for the unit sphere
Python package implementing ideal and shrinkage-based geodesic slice samplers defined on the n-sphere.
Implementation of uniformity tests on the circle and (hyper)sphere, with a C++ core. The package allows the replication of the data application in "On a projection-based class of uniformity tests on the hypersphere"
Nonparametric kernel density estimation, bandwidth selection, and other utilities for analyzing directional data
Code for "Deep Orientaton Uncertainty Learning based on a Bingham Loss" (ICLR2020)
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