Day/Time: Thursdays 5:10-7:00pm
Location: CIWW 312
Generative models define procedures that produce samples of data. They can be used to learn representations, to handle exploration/exploitation tradeoffs, and to make use of the large amounts of unlabeled data. Deep generative models use ideas from deep learning to build generative models and algorithms for learning them. This course will focus on some of the recent advances in deep generative models. Students will embark on a semester-long research project around deep generative models.