expectation-maximization

je-suis-tm/machine-learning

Python machine learning applications in image processing, recommender system, matrix completion, netflix problem and algorithm implementations including Co-clustering, Funk SVD, SVD++, Non-negative Matrix Factorization, Koren Neighborhood Model, Koren Integrated Model, Dawid-Skene, Platt-Burges, Expectation Maximization, Factor Analysis, ISTA, FISTA, ADMM, Gaussian Mixture Model, OPTICS, DBSCAN, Random Forest, Decision Tree, Support Vector Machine, Independent Component Analysis, Latent Semantic Indexing, Principal Component Analysis, Singular Value Decomposition, K Nearest Neighbors, K Means, Naïve Bayes Mixture Model, Gaussian Discriminant Analysis, Newton Method, Coordinate Descent, Gradient Descent, Elastic Net Regression, Ridge Regression, Lasso Regression, Least Squares, Logistic Regression, Linear Regression

psaris/funq

Source files for "Fun Q: A Functional Introduction to Machine Learning in Q"

mr-easy/GMM-EM-Python

Python implementation of EM algorithm for GMM. And visualization for 2D case.

Labo-Lacourse/stepmix

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.

cambridge-mlg/DUN

Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)

m-clark/models-by-example

By-hand code for models and algorithms. An update to the 'Miscellaneous-R-Code' repo.

soroosh-rz/Bayesian-Methods-for-Machine-Learning

Bayesian Methods for Machine Learning

sukrutrao/Fast-Dawid-Skene

Code for the algorithms in the paper: Vaibhav B Sinha, Sukrut Rao, Vineeth N Balasubramanian. Fast Dawid-Skene: A Fast Vote Aggregation Scheme for Sentiment Classification. KDD WISDOM 2018

GFNOrg/GFlowNet-EM

Code for GFlowNet-EM, a novel algorithm for fitting latent variable models with compositional latents and an intractable true posterior.

ajcr/em-explanation

Notebooks explaining the intuition behind the Expectation Maximisation algorithm

manuwhs/Trapyng

Python library to implement advanced trading strategies using machine learning and perform backtesting.

moucheng2017/EM-BPL-Semi-Seg

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

corradomonti/learnable-opinion-dynamics

Code and data for the KDD2020 paper "Learning Opinion Dynamics From Social Traces"

davpinto/ml-simulations

Animated Visualizations of Popular Machine Learning Algorithms

dmetivie/ExpectationMaximization.jl

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

andreacasalino/Gaussian-Mixture-Model

C++ library handling Gaussian Mixure Models

francois-rozet/diem

Official implementation of Learning Diffusion Priors from Observations by Expectation Maximization

Xinglab/CLAM

CLIP-seq Analysis of Multi-mapped reads

yashv28/Color-Segmentation-using-GMM

hrshtv/HMRF-GMM-EM-Segmentation

Image segmentation using the EM algorithm that relies on a GMM for intensities and a MRF model on the labels. Based on "Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm" (Zhang, Y et al.)

ali92hm/expectation-maximization

An implementation of the expectation maximization algorithm

dpeerlab/scKINETICS

Code for scKINETICS (ISMB 2023)

agrawal-priyank/machine-learning-clustering-retrieval

Built text and image clustering models using unsupervised machine learning algorithms such as nearest neighbors, k means, LDA , and used techniques such as expectation maximization, locality sensitive hashing, and gibbs sampling in Python

mgaynor1/nQuack

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

polyactis/Accucopy

Accucopy is a computational method that infers Allele-Specific Copy Number alterations from low-coverage low-purity tumor sequencing data.

haplotype/ELAI

Efficient Local Ancestry Inference

kashefy/mi2notes

My notes for Prof. Klaus Obermayer's "Machine Intelligence 2 - Unsupervised Learning" course at the TU Berlin

ludovicdmt/gpu_gmm

GPU traning of a Gaussian Mixture (with online EM)

elifyilmaz2027/projects

This is the repository containing machine learning and deep learning projects, as well as some presentation slides on these topics.

huajh/variational_bayesian_clusterings

variational Bayesian algorithm for Brain MR image Segmentation

kailugaji/Gaussian_Mixture_Model_for_Clustering

Gaussian Mixture Model for Clustering

popolee0513/Data-Science-Skills-Practice

akash18tripathi/Gaussian-Mixture-Models-for-Background-Extraction

This repository contains a Jupyter Notebook that implements Gaussian Mixture Model (GMM) for semantic segmentation and background extraction. GMM class is implemented from scratch without using any libraries like sklearn.

navreeetkaur/bayesian-network-learning

Learning Bayesian Network parameters using Expectation-Maximisation

zhuwei-ZJU/EM-for-BAYOMA

Bayesian operational modal analysis based on the expectation-maximization algorithm.