https://github.com/wiseodd/probabilistic-models

Collection of probabilistic models and inference algorithms
https://github.com/wiseodd/probabilistic-models

bayesian bayesian-inference dirichlet-process gibbs-sampling machine-learning mcmc probabilistic-models python variational-inference

Last synced: 8 months ago
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Collection of probabilistic models and inference algorithms

• Host: GitHub
• URL: https://github.com/wiseodd/probabilistic-models
• Owner: wiseodd
• License: bsd-3-clause
• Created: 2016-12-24T02:51:45.000Z (almost 9 years ago)
• Default Branch: master
• Last Pushed: 2020-04-03T12:27:08.000Z (over 5 years ago)
• Last Synced: 2025-04-04T14:49:09.512Z (9 months ago)
• Topics: bayesian, bayesian-inference, dirichlet-process, gibbs-sampling, machine-learning, mcmc, probabilistic-models, python, variational-inference
• Language: Python
• Homepage: https://wiseodd.github.io
• Size: 26.4 KB
• Stars: 241
• Watchers: 15
• Forks: 76
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Probabilistic Models

Collection of examples of various probabilistic models and inference algorithms.

### Dependencies

1. Python 3

2. Numpy

3. Matplotlib

## List of Models/Algorithms

### Bayesian Inference

1. Bayesian Linear Regression

2. Gaussian Mixture Model (GMM) with:

    1. Gibbs Sampler

    2. Mean-field Variational Inference

3. LDA with:

    1. Gibbs Sampler

    2. Collapsed Gibbs Sampler

    3. Mean-field Variational Inference

4. Bayesian Dark Knowledge (SGLD + Distillation)

### Bayesian Non-parametric

1. Gaussian Process Regression

2. GMM with CRP prior for Infinite Mixture Model

3. Generative stories:

    1. Chinese Restaurant Process (CRP)

    2. Stick Breaking Construction

    3. Indian Buffet Process (IBP)

### Others (MLE)

1. Probabilistic Linear Regression

2. Mixture of Linear Regression with EM

3. GMM with EM