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