Hidden Markov Models with Directional Distributions for EEG data modeling
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Updated
Sep 12, 2022 - Python
Hidden Markov Models with Directional Distributions for EEG data modeling
A companion repository for 'Inverse Bayesian Optimization: Learning Human Acquisition Functions in an Exploration vs Exploitation Search Task'
Uniformization tool for directional statistics on sphere
Bingham Distribution Directional Statistics Library in Eigen3 / C++17
A set of Course projects developed during the MSc on Mathematical Modelling and Computation at DTU
A directional-linear finite mixture model for clustering
Tests for rotational symmetry on the hypersphere. Software companion for "On optimal tests for rotational symmetry against new classes of hyperspherical distributions"
Implementation of the Expectation Maximization Algorithm for Hidden Markov Models including several Directional Distributions
Python package implementing ideal and shrinkage-based geodesic slice samplers defined on the n-sphere.
Directional Co-clustering with a Conscience (DCC)
PCA on the torus using density ridges. Software companion for "Toroidal PCA via density ridges"
A curated BibTeX file with more than 1700 contributions in Directional Statistics
Spherical statistics in Python
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)
Clustering routines for the unit sphere
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