out March 2, due March 16, 2022 (23:59:59)
In this homework, you will implement and train a variety of different autoregressive models, mainly PixelCNN and its variants. For a detailed description of the assignment, please refer to this Github repository.
out March 21, due April 8, 2022 (23:59:59)
In this homework, you will implement and train a normalizing flow model, RealNVP, and various VAE models. For a detailed description of the assignment, please refer to this Github repository.
out April 10, due May 1, 2022 (23:59:59)
In this homework, you will implement and train CycleGAN and a diffusion-based model. For a detailed description of the assignment, please refer to this Github repository.
Late Policy:You may use up to 7 grace days (in total) over the course of the semester. That is, you can submit your solutions without any penalty if you have free grace days left. Any additional unapproved late submission will be punished (1 day late: 20% off, 2 days late: 40% off, 3 days late: 50% off). Note that no submission after 3 days will be accepted -- you may use at most 3 grace days for a specific assignment.