# 🔍 Semantic Article RecommenderThis project offers a simple way to find articles that are similar in meaning. It uses advanced techniques like Hugging Face embeddings and FAISS for efficient searching. 🛠️

Some notes on algorithms for time series and sequential data

A package for parameter estimation of Linear-Gaussian state-space models, specialized for neuroimaging analysis

A LibreOffice Calc extension that clusters the rows in a table and colors them to indicate the clusters.

An R package for predicting ploidal level from sequence data using site-based heterozygosity 

Apply different clustering methods

A Python package following the scikit-learn API for model-based clustering and generalized mixture modeling (latent class/profile analysis) of continuous and categorical data. StepMix handles missing values through Full Information Maximum Likelihood (FIML) and provides multiple stepwise Expectation-Maximization (EM) estimation methods.

A simple but generic implementation of Expectation Maximization algorithms to fit mixture models.

The multi-sample Gaussian mixture model (MSGMM) is a clustering model adapted to fitting multiple samples simultaneously using the EM algorithm.

This project consists of comparative algorithm analysis between six machine learning algorithms to identify the optimum ML algorithm for intrusion detection.

R package for fitting mixture distributions to data using various approaches

MATLAB codes for paper: Tractable Maximum Likelihood Estimation for Latent Structure Influence Models with Applications to EEG & ECoG processing

[MICCAI 2022 Best Paper Finalist] Bayesian Pseudo Labels: Expectation Maximization for Robust and Efficient Semi Supervised Segmentation

Halfmoons dataset - perceptron, least squares, GMM and RBF solutions.

Image Clustering Algorithm implemented in C++

Official implementation of Learning Diffusion Priors from Observations by Expectation Maximization

This contains my course assignments of SEM 3

Estimation of Gaussian Bernoulli Mixture - Latent Class Choice Models (GBM-LCCM) using the Expectation Maximization (EM) algorithm

Estimation of Gaussian Process - Latent Class Choice Models (GP-LCCM) using the Expectation Maximization (EM) algorithm

A lightweight particle filter library for the ROS context.