Deep Generative Models (Pengtao Xie)

Graphical Models

• Lecture 1: Introduction and Bayesian Network

Inference

• Lecture 2: Variational Inference
• Lecture 3: Variational Autoencoder (VAE)

Parameter Learning

• Lecture 4: Maximum Likelihood and EM Algorithm

Deep Generative Models

- Generative Adversarial Network (GAN)

• Lecture 5: Introduction to GAN

- Large Language Model (LLM)

• Lecture 6: Introduction to LLM
• Lecture 7: Multi-modal LLM and Parameter-Efficient Finetuning
• Lecture 8: LLM Reasoning
• Lecture 9: LLM Agent

- Diffusion Model

• Lecture 10: Denoising Diffusion Model
• Lecture 11: Score-based Diffusion Model

Implementation of Deep Generative Models

• Lecture 12 (Guest Lecture): Implementation of Variational Autoencoder
• Lecture 13 (Guest Lecture): Implementation of Generative Adversarial Network
• Lecture 14 (Guest Lecture): Implementation of LLM (I): Transformer and language model
• Lecture 15 (Guest Lecture): Implementation of LLM (II): Multi-modal LLM and parameter-efficient finetuning
• Lecture 16 (Guest Lecture): Implementation of Denoising Diffusion Model
• Lecture 17 (Guest Lecture): Implementation of Score-based Diffusion Model

Advanced Topics and Course Project Presentation

• Lecture 18: World Models
• Lecture 19: Course Project Presentation (I)
• Lecture 20: Course Project Presentation (II)