All models are wrong, but some are useful -- George Box

Topics

The goal is to learn machine learning by reading and discussing Kevin Murphy’s recent book and some important machine learning papers together. The tentative topics that will be covered in this course

• Bayesian machine learning
• Probabilistic graphical models
• Variational inference
• Monte Carlo inference
• Deep neural networks
• Bayesian neural networks
• Variational autoencoders
• Generative adversarial networks

Reference

Textbook

• Kevin Murphy. Probabilistic Machine Learning: Advanced Topics. May 2nd, 2022

Research Papers

• TODO