{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Bayesian Probabilistic Matrix Factorization\n", "\n", "**Published**: November 6, 2020\n", "\n", "**Author**: Xinyu Chen [[**GitHub homepage**](https://github.com/xinychen)]\n", "\n", "**Download**: This Jupyter notebook is at our GitHub repository. If you want to evaluate the code, please download the notebook from the [**transdim**](https://github.com/xinychen/transdim/blob/master/imputer/BPMF.ipynb) repository.\n", "\n", "This notebook shows how to implement the Bayesian Probabilistic Matrix Factorization (BPMF), a fully Bayesian matrix factorization model, on some real-world data sets. For an in-depth discussion of BPMF, please see [1].\n", "\n", "