Course-Specific Resources

The syllabus for the course is here:

• Syllabus on RPI Box

We will be following the Foster textbook below closely (as well as additional papers linked in the page for each lecture).

• Generative Deep Learning: Teaching Machines To Paint, Write, Compose, and Play, 2nd Edition by David Foster, O’Reilly Media, June 2023

These books on deep learning may also be useful as reference.

• Learning Deep Learning by Magnus Ekman, Perason, August 2021
• Understanding Deep Learning by Simon Prince, MIT Press, December 2023

Supplemental Videos

• Probability Bites by Rich Radke
• Graphics in 5 Minutes by Steve Seitz

Related Courses from Other Universities

• MIT 6.S192: Deep Learning for Art, Aesthetics, and Creativity
• Stanford CS236: Deep Generative Models
• Berkeley CS294: Deep Unsupervised Learning
• University of Washington CSE 599: Generative Models
• University of Illinois ECE 598: Generative AI Models
• Bradley University: Critical Topics AI Images

RPI Links

• Student Rights, Responsibilities, and Conduct
• Counseling Center