The goal of this course is to familiarize students with the basics of probabilistic modeling in machine learning, with a strong focus on deep probabilistic models. Students will read and discuss recent research papers, as well as conduct a research project.
Course Description
- Research-oriented course. Students will present lectures and conduct a research project.
- Lectures on Tu/Th 10.30am-11:55am in Annenberg 105
- First lecture: 4/2/2019
- Piazza: https://piazza.com/class/jtzcdq4chpm5wq
Evaluation
- Lecture presentation: 20%
- Final project (Report + poster session): 80%
- See Project Guidelines.
- Project Proposal Due April 26th.
- Project Report Due
- June 7th by 5pm for groups containing graduate students or graduating seniors.
- June 12th by 5pm for groups containing only non-graduating undergraduates.
- Poster Session June 6th during class hours.
Prerequisites:
- CS 155 or permission from instructor
Instructor
Main TAs:
Secondary TAs: