The Chinese University of Hong Kong AIST 5030: Generative Artificial Intelligence Spring 2025 Home | Grading | Schedule | Resource | Piazza | Canvas

 

Courses

• CS236: Deep Generative Models (Stanford University): Course website
• 6.S978: Deep Generative Models (MIT), Course website
• Deep Learning (Imperial College), Course website

Books

Computer vision:

• [Sz] Szeliski, Computer Vision: Algorithms and Applications, Springer, 2010 (online draft)
• [HZ] Hartley and Zisserman, Multiple View Geometry in Computer Vision, Cambridge University Press, 2004
• [FP] Forsyth and Ponce, Computer Vision: A Modern Approach, Prentice Hall, 2002
• [Pa] Palmer, Vision Science, MIT Press, 1999

Learning:

• [GBC] Goodfellow, Bengio, Courville, Deep Learning, MIT Press, 2016
• [Mi] Mitchel, Machine Learning, McGraw-Hill, 1997
• [DHS] Duda, Hart and Stork, Pattern Classification (2nd Edition), Wiley-Interscience, 2000
• [SB] Sutton & Barto, On-line book. The classic reference to the field of reinforcement learning.

Graphical models:

• [KF] Koller and Friedman, Probabilistic Graphical Models: Principles and Techniques, MIT Press, 2009