EE 641: Deep Learning Systems
University of Southern California, Fall 2026
Schedule
Week 1
| Aug 26 |
Homework 1HW 1 assigned
|
Week 2
| Sep 2 |
Lecture 2Object detection and segmentation
Homework 2Multi-Scale Detection and Spatial Regression
|
Week 3
| Sep 9 |
Lecture 3Multi-scale detection and spatial regression
|
Week 4
| Sep 16 |
Lecture 4Generative Models: Energy-Based Models, GANs, and VAEs
Homework 3Generative Adversarial Networks and Variational Autoencoders
|
Week 5
| Sep 23 |
Lecture 5Generative models, continued. Recurrent Neural Networks and Sequence-to-Sequence Models
|
Week 6
| Sep 30 |
Lecture 6Attention mechanisms and self-attention
Homework 4Attention Mechanisms and Transformers
|
Week 7
| Oct 7 |
Lecture 7Transformers. Large language models (LLMs) and Mixture of experts (MoE)
|
Week 8
| Oct 14 |
Lecture 8Reinforcement learning principles
Homework 5HW 5 assigned
ProjectProject Overview
|
Week 9
| Oct 21 |
Lecture 9Reinforcement learning applications
|
Week 10
| Oct 28 |
ExamExam (weeks 4-9)
|
|
| Nov 2 |
ProjectDraft project proposal due, 23:59
|
Week 11
| Nov 4 |
Project proposal meetings
|
|
| Nov 6 |
ProjectRevised project proposal due
|
No class, Veterans Day (Nov 11)
Week 12
| Nov 18 |
Project meetings
|
|
| Nov 23 |
ProjectStatus report due
|
No class, Thanksgiving Holiday (Nov 25)
Week 13
| Dec 2 |
Project presentations (mandatory) - EXTENDED TIME
|
Project deliverables due Sunday, December 6 at 23:59
No matching items