Source code for the Bayesion Machine Learning project on Stein Variational Gradient Descent

Analysis of the paper A Non-Asymptotic Analysis for Stein Variational Gradient Descent, and detailed summary of the theoretical results of SVGD for the Bayesian Machine Learning course at the MVA master at ENS Paris-Saclay.

One might want to read the report first.

We also provide an implementation of the SVGD algorithm using Numpy.

Usage

Install the required packages by running:

pip install -r requirements.txt

if you don't.

Then, run the code by running:

python main.py nb_iterations

it will run both experiments detailed in the report and save all the figures in a exp[1-2] folder.