# sampling-methods-numpy

**Repository Path**: teddy-zhu/sampling-methods-numpy

## Basic Information

- **Project Name**: sampling-methods-numpy
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-08-28
- **Last Updated**: 2025-08-28

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# Sampling Methods in Numpy

This repository contains code for some basic sampling methods implemented using numpy.    

The following methods are implemented with examples

* Importance Sampling (Univariate example)
* Rejection Sampling (Univariate example)
* Metropolis-Hastings (Univariate and Multivariate example)
* Gibbs Sampling (Multivariate example)
* Langevin Monte Carlo
  * Unadjusted Langevin Algorithm (ULA) - Pytorch
  * Metropolis-adjusted Langevin Algorithm (MALA) - Pytorch
* Inverse Transform Sampling
  * Cauchy Distribution
  * Exponential Distribution
  * Gumbel Distribution