Organization of synaptic connectivity as the basis of neural computation and learning. Perceptrons, convolutional nets, transformers, and diffusion models. Engineering applications including computer vision and natural language processing.

Requirements

  • Two 80 minute lectures per week.
  • Grades (A-F) will be based on class participation (5%), problem sets (25%), in-class exams (40%), and final project (30%).
  • Participation includes speaking up in lecture and precept.
  • Participation also includes activity on Ed—ideally asking good questions, giving good answers, and upvoting others’ contributions.

Prerequisites

  • Ideally you should have taken COS 324
  • Familiarity with linear algebra.
  • Basics of optimization and probability theory.
  • Knowledge of Python (or willingness to learn).

Lectures

Prof. Sebastian Seung will lecture twice a week.

TAs

  • Jiayi Geng
  • Chenyue Cai
  • Hongyu Wen

Office Hours

  • Th 10:00-10:50pm Sherrerd H 001 (Chenyue Cai)
  • Th 7:30-8:20pm Sherrerd H 001 (Hongyu Wen)

For students who can’t attend these hours, additional office hours with Jiayi Geng are available by appointment.

Online discussions

You can ask and answer questions on the Ed site. Ed activity counts as class participation and can enhance your grade.

Final Project Guidelines

There will be no final exam in this class. Instead, a final project will be worth 25% of your grade. More details will be posted later on.

Homework assignments

Homework assignments will be due on Fridays, and should be submitted on gradescope.

Homework late policy

There is a accumulated percentage drop on the overall points of 20% per day (eg. 2 days late => -40%). If you have reasons (eg. conference, illness, …) for why you cannot make a deadline, write us (all instructors) an E-mail before the deadline including a suggested new deadline. We will grant requests on an individual basis.