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VOOZH | about |
Python library for analysis of time series data including dimensionality reduction, clustering, and Markov model estimation
Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python
World beating online covariance and portfolio construction.
Lightweight robust covariance estimation in Julia
Implementation of linear CorEx and temporal CorEx.
Mean and Covariance Matrix Estimation under Heavy Tails
R Package: Regularized Principal Component Analysis for Spatial Data
Implementation of the Paper "Channel Estimation for Quantized Systems based on Conditionally Gaussian Latent Models".
PCA, Factor Analysis, CCA, Sparse Covariance Matrix Estimation, Imputation, Multiple Hypothesis Testing
Framework for estimating parameters and the empirical sandwich covariance matrix from a set of unbiased estimating equations (i.e. M-estimation) in R.
gips - Gaussian model Invariant by Permutation Symmetry
Code for NeurIPS 2025 paper - Covariances for Free: Exploiting Mean Distributions for Training-free Federated Learning
R code and dataset for the paper on spatially functional data
General purpose correlation and covariance estimation
Unidimensional trivial Kalman filter (header only, Arduino compatible) library
Code for implementing Factor Analysis with BLEssing of dimensionality (FABLE).
R package for Partially Separable Multivariate Functional Data and Functional Graphical Models
A Python front-end for the large-scale graphical LASSO optimizer BigQUIC (written in R).
This repository contains iPython notebooks that run on the octave kernel to accompany tutorial and slides presented at PRNI
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