Useful Machine Learning Materials and Resources

This post is a place for me to put all machine learning resources that I think it is great.

Language Models

• LLM Timeline

Generative Models

• Auto-Regressive Generative Models
  • Intro to Pixel Recurrent Neural Networks - Logan Lebanoff
• Flow Models
  • Flow-based Deep Generative Models - Lilian Weng
  • Tutorial 11 (JAX): Normalizing Flows for image modeling - UvA DL Notebooks
  • Variational Dequantization - Akihiro Matsukawa
• Diffusion Models and Score-Based Models
  • Diffusion models are autoencoders
  • Score-Based Generative Models

Binding Problem

• Survey
  • On the Binding Problem in Artificial Neural Networks - Klaus Greff, Sjoerd van Steenkiste, Jürgen Schmidhuber
• Philosophy
  • On the Measure of Intelligence - François Chollet

System Stuffs

• Large Scale Training
  • How to Train Really Large Models on Many GPUs? - Lilian Weng
• Neural Network Components
  • CNN implementation - Anirudh Shenoy

Software Engineering

• Writing Code for NLP Research

Misc

• Research Engineering FAQs
• How to Read a Paper - S. Keshav

Update history

• 08-31-2023: add LLM timeline
• 05-10-2023: add paper “On the Measure of Intelligence”
• 02-08-2023: add “CNN implementation - Anirudh Shenoy”