CS394N, NEU394P Neural Networks-WB

Fall 2022, Wed 10:30am-12pm & Wed 1:30-3pm CT, Online
Unique numbers 53100 (CS394N), 56365 (NEU394P)
Zoom links to class meetings and office hours are in Canvas
Risto Miikkulainen
Office hrs (online; until 12/12/22; exceptions):
Drop-in: Mon 1-1:30pm CT; By appt: Fri 2-3pm CT

Ishan Nigam
Office hrs (online): Mon 2-3pm CT; or by appointment

- C. Aggarwal (2018). Neural Networks and Deep Learning. New York: Springer. (required).
- Various research papers (some required, some optional).

Course organization:
This course is fully online, but synchronous. That is, we follow the same structure as we would in an in-person class, but participate through videoconference.

30% Exam on introductory lectures
20% Homework assignments
10% Questions on topic talks
40% Project paper
- No makeup exams without a valid proof of unexpected emergency.
- Turning homework in late will reduce the grade 15% for the first 24hrs, 40% for the second, 75% for the third, and 100% after that.
- Plus/minus final grades will be used; attendance will not affect the final grade.
- Students with disabilities may request appropriate academic accommodations from the Services for Students with Disabilities.
- Cheating will not be tolerated; see CS Department Code of Conduct

More details:
Course Description
Class Schedule
Homework Assignments
Topic Talks
Project Talks
Project Papers
Class Resources

The UTCS Neural Networks Research Group
Advice for Graduate Students

Sat Aug 27 20:37:02 CDT 2022