# References for Probability Estimation Club

## #Bayesian #Least Squares #Bootstrap #Maximum Likelihood #Bayesian #Normalizing Flow

A list of references for our online discussions.

This is Not a Comprehensive List. Please also see the references from each event.

Conditional Probability Estimation

An online journal club on the topics Conditional Probability Estimation. Our cover topics on all sorts of probabilistic approach, such as VAE, normalizing, graph neural network, probabilistic time series forecasting.

## Basics

- Trevor Hastie, Robert Tibshirani, J. F. (2004). The Elements of Statistical Learning (Vol. 99, Issue 466). Springer Science & Business Media.
- Christpher M. Bishop. (2006). Pattern Recognition and Machine Learning.

### Normalizing Flow

## Energy-based Models

- Pytorch Deep Learning Lectures
- Pytorch Deep Learning Slides
- A high-bias, low-variance introduction to Machine Learning for physicists

## ML Connections to Biological Networks

## Graph Neural Networks

Planted:
by LM;

## Table of Contents

**Current Ref:**

- cpe/00.references.md