Different optimization algorithms like Hill climbing, Simulated annealing, Late accepted Hill climbing , Genetic Algorithm is implemented from scratch.

Code accompanying the paper "Globally Optimal Learning for Structured Elliptical Losses", published at NeurIPS 2019

Implementation of the Paper "Channel Estimation for Quantized Systems based on Conditionally Gaussian Latent Models".

A Python front-end for the large-scale graphical LASSO optimizer BigQUIC (written in R).

Implementation of linear CorEx and temporal CorEx.

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