https://github.com/koriavinash1/pgm

Graph: Representation, Learning, and Inference Methods
https://github.com/koriavinash1/pgm

active-trails bayesian-inference bayesian-network bfs bn-representation dfs gibbs-sampling gibbs-sampling-algorithm graph inference loopy-belief-propagation markov-networks message-passing-interface metropolis-hastings pgm pgm-inference pgm-learning pgm-representation probability

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Graph: Representation, Learning, and Inference Methods

• Host: GitHub
• URL: https://github.com/koriavinash1/pgm
• Owner: koriavinash1
• License: mit
• Created: 2020-02-25T03:56:24.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2022-06-22T01:50:20.000Z (over 2 years ago)
• Last Synced: 2024-09-07T02:28:45.903Z (2 months ago)
• Topics: active-trails, bayesian-inference, bayesian-network, bfs, bn-representation, dfs, gibbs-sampling, gibbs-sampling-algorithm, graph, inference, loopy-belief-propagation, markov-networks, message-passing-interface, metropolis-hastings, pgm, pgm-inference, pgm-learning, pgm-representation, probability
• Language: Python
• Size: 253 KB
• Stars: 4
• Watchers: 3
• Forks: 0
• Open Issues: 3
• Metadata Files:
  • Readme: README.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md

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README

        
# PGM

[![Build Status](https://travis-ci.org/koriavinash1/pgm.svg?branch=master)](https://travis-ci.org/koriavinash1/pgm)

[![Documentation Status](https://readthedocs.org/projects/ppgm/badge/?version=latest)](https://ppgm.readthedocs.io/en/latest/?)

[![PyPI version](https://badge.fury.io/py/ppgm.svg)](https://badge.fury.io/py/ppgm)

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

Probabilistic graphs: Representation, Learning, and Inference

## Features

- [x] Representation

  - [x] Bayesian Network Representation

  - [x] Linked List BN Representation

  - [x] Linked List MN Representation

  - [ ] Conditional Estimation

  - [ ] Marginal Estimation

  - [ ] Joint Estimation

- [x] Inference

  - [x] Metropolis-Hastings algorithm

  - [x] Gibbs Sampling on 2d grid

  - [ ] Generalized Gibbs Sampling

  - [x] Message Parsing and BP

  - [x] Loopy BP

  - [x] VE

  - [ ] Causal Interventions

- [x] search methods

  - [x] DFS

  - [x] BFS

- [x] Additional

  - [x] Finding Active Trails

  - [ ] Max clique size and clique node

  - [ ] Calculate tree-width

- [ ] Learning 

- [x] Miscellaneous

  - [x] Random BN and MN generation

 

## Installation

```

pip install ppgm

```

  

## Contact

- Avinash Kori ([email protected])