Probabilistic Models Save

Collection of probabilistic models and inference algorithms

Project 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
Open Source Agenda is not affiliated with "Probabilistic Models" Project. README Source: wiseodd/probabilistic-models

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