Calendar

Note: This course website is still under development and is subject to change.

Week 1

Jan 8

Lec 1 Course Introduction: Recording

Project 0 out

Week 2

Jan 13

Lec 2 Image Classification: Recording

: 📖 GBC Ch. 1

: 📖 231n Image Classification

Jan 14

Dis 1 Intro to Python and Pytorch: Recording

Jan 15

Lec 3 Linear Classifiers

Project 1 out: 📖 231n Linear Classification

Jan 19

Project 0 due

Week 3

Jan 20

MLK Day-No Class

Jan 21

Dis 2 Intro to PROPS Dataset

: 📖 Chen et al., ProgressLabeller

Jan 22

Lec 4 Regularization + Optimization: 📖 231n Optimization

: 📖 GBC Sec 8.1-8.6

: 📖 Li et al., Visualizing Loss Landscaps

: 📖 Goh, Why Momentum Really Works

Week 4

Jan 27

Lec 5 Neural Networks I

: 📖 231n Neural Networks

: 📖 GBC Sec 6.1-6.4

Jan 28

Dis 3 Neural Networks II

: 📖 Nielsen, Universal Approximation

Jan 29

Lec 6 Backpropagation

Project 2 out: 📖 cs231n Backpropagation

: 📖 GBC Sec 6.5-6.6

: 📖 Olah, Backpropagation

Feb 2

Project 1 due

Week 5

Feb 3

Lec 7 Convolutional Neural Networks

: 📖 cs231n ConvNets

: 📖 GBC Ch. 9

: 📖 Araujo et al., Receptive Fields of CNNs

: 📖 Olah et al., Feature Visualization

Feb 4

Dis 4 CNN Object Detection Demo

Feb 5

Lec 8 CNN Architectures I

: 📖 Krizhevsky et al., AlexNet

: 📖 Simonyan and Zisserman, VGG

: 📖 Szegedy et al., GoogLeNet

: 📖 He et al., ResNet

Week 6

Feb 10

Lec 9 CNN Architectures II

: 📖 Girshick et al., R-CNN

: 📖 Redmon et al., YOLO

: 📖 Lin et al., FCOS

Feb 11

Dis 5 P2 Help

: 📖 Krizhevsky et al., AlexNet

Feb 12

Lec 10 Object Detection

Project 2 due Project 3 out: 📖 cs231n Training I

: 📖 Olah et al., Equivariance in Networks

Week 7

Feb 17

Lec 11 Training Neural Networks I

: 📖 cs231n Training II

: 📖 Goodfellow et al., Adversarial Examples

Feb 18

Dis 6 Training Neural Networks II

: 📖 cs231n Training II

Feb 19

Lec 12 Deep Learning Software

: 📖 Redmon, Darknet

: 📖 Jia et al., Caffe

: 📖 Abadi et al., TensorFlow

: 📖 Paszke et al., PyTorch

Week 8

Feb 24

Lec 13 Pose Estimation

: 📖 Xiang et al., PoseCNN

: 📖 Mildenhall et al., NeRF

Feb 25

Dis 7 How to Read Research Papers: 📖 Vannevar Bush, Science The Endless Frontier

Feb 26

Lec 14 Final Project Topics

Project 3 due

Spring Break

Mar 3: Break
Mar 4: Break
Mar 5: Break

Week 9

Mar 10

Lec 15 RGB-D Architectures

: 📖 Xiang, PoseCNN

: 📖 Wang, DenseFusion

Mar 11

Dis 8 Midterm Review

Mar 12

Lec 16 Midterm

Project 4 out

Week 10

Mar 17

Lec 17 Transformers

: 📖 Vaswani, Attention Is All You Need

Mar 18

Dis 9 Generative Models

Mar 19

Lec 18 Vision Transformers

: 📖 Dosovitskiy, ViT

: 📖 Carion, DETR

: 📖 Xie, SegFormer

Week 11

Mar 24

Lec 19 Vision-Language Models

: 📖 Devlin, BERT

: 📖 Radford, CLIP

: 📖 Kerr, LERF

Mar 25

Dis 10 P4 Help

Mar 19

Lec 20 Transformer Applications

Project 4 Due

Week 12

Mar 31: Lec 21 Interpretability and Uncertainty
Apr 1: Dis 11 Final Project Proposals
Apr 2: Lec 22 Challenges in DL

Week 13

Apr 7: Lec 23 NeRF & Gaussian Splatting
Apr 8: Dis 12 Final Project Help
Apr 9: Lec 24 Deep Reinforcement Learning

Week 14

Apr 14: Lec 25 Invited Speaker
Apr 15: Dis 13 Final Project Help
Apr 16: Lec 26 Invited Speaker

Week 15

Apr 21: Lec 27 Invited Speaker
Apr 22: Dis 14 Final Project Help
Apr 23: Lec 28 No Class

Week 16

Apr 28: No Class; Final Project Due