This research project will illustrate the use of machine learning and deep learning for predictive analysis in industry 4.0.

A library providing math and statistics operations for numbers of arbitrary size.

Gauss Naive Bayes in Python From Scratch.

Estimation of Distribution algorithms Python package

The algorithm solves the DC state estimation problem in electric power systems using the Gaussian belief propagation over factor graphs.

The FactorGraph package provides the set of different functions to perform inference over the factor graph with continuous or discrete random variables using the belief propagation algorithm.

"Gaussian RAM: Lightweight Image Classification via Stochastic Retina Inspired Glimpse and Reinforcement Learning" (ICCAS 2020)

pg_math extension to support statistical distribution functions for PostgreSQL

Official project of DiverseSampling (ACMMM2022 Paper)

Modern C++ library handling gaussian processes

A MATLAB project which applies the central limit theorem on PDFs and CDFs of different probability distributions.

Surface water quality data analysis and prediction of Potomac River, West Virginia, USA. Using time series forecasting, and anomaly detection : ARIMA, SARIMA, Isolation Forest, OCSVM and Gaussian Distribution

Gaussian belief propagation solver for noisy linear systems with real coefficients and variables.

TensorFlow implementation of "A Simple Baseline for Bayesian Uncertainty in Deep Learning"

PyPi package for modelling Probability distributions

Fast Gaussian distributed pseudorandom number generation in Java via the Ziggurat algorithm

Longtail transforms RV from the given empirical distribution to the standard normal distribution

C++ and Julia Normal distribution generated with uniform distribution

This repository contains implementation of Neural Network,k-Means and Gaussian Mixture Models with Python

A Proof-of-Concept implementation of the homomorphic encryption scheme by Yoshinori Aono et al.