Date | Topic | Reading | Student Presentation | Assignments |
1. Aug 23 | Introduction / overview (pdf) | | | |
2. Aug 25 | Basics of machine learning: simple learning models, supervised vs unsupervised learning, overfitting (pdf) | Goodfellow 5-5.2.0, 5.3 | | |
3. Aug 30 | Basics of neural networks: feedforward neural networks, autoencoders (pdf) | Goodfellow 6, 6.1, 6.4, 14, 14.1, 14.9 | | |
4. Sept 1 | Training neural networks I: automatic differentiation, backpropagation, stochastic gradient descent (pdf) | Goodfellow 4.3, 5.9, 6.5, blog | | |
5. Sept 6 | Training neural networks II: initialization, dropout, vanishing gradients problem, batch normalization, softmax (pdf) | Goodfellow 7.12, 8.4, 8.7.1 | | |
6. Sept 8 | Classical computer vision: manual feature engineering (pdf) | Lowe 2004 | | |
7. Sept 13 | Convolutional neural networks (CNNs): convolution and pooling layers, residual networks (pdf) | Goodfellow 9-9.3, [1] | | |
8. Sept 15 | Recurrent neural networks (RNNs) and Long Short Term Memory (LSTM) (pdf) | Goodfellow 10-10.2.2, 10.10.1 | | |
9. Sept 20 | Training neural nets in practice: fine-tuning, data augmentation, Torch | Goodfellow 15.2, 7.4 | | |
10. Sept 22 | Applications to natural language processing, finance | [1], [2] | | |
11. Sept 27 | Applications to games and robotics; reinforcement learning (pdf) | [1], [2], [3], [4] | | Assignment 1 due |
12. Sept 29 | Computer vision: image recognition and object detection | [1], [2], [2b], [2c], [2d] | | |
Reading days: Oct 1 - 4 | | | | |
13. Oct 6 | Computer vision: semantic segmentation and inpainting | [1], [2], [3] | | |
14. Oct 11 | Computer vision as inverse computer graphics I | [1], [2] | | |
15. Oct 13 | Computer vision as inverse computer graphics II | [1], [2], [3] | | |
16. Oct 18 | Visualizing convolutional neural networks | [1], [2] | | |
17. Oct 20 | Novel image synthesis / audio synthesis | [1], [2], [3], [4], music: [5], [6] | | |
18. Oct 25 | Computer graphics: composite image generation | [1], [2], [3], [4] (video: [4]) | | |
19. Oct 27 | Computer graphics: photo albums | [1], [2] | | |
20. Nov 1 | Computer graphics: style transfer, portraits | [1], [2], [3] | | |
21. Nov 3 | Computer graphics: portraits, 3D labeling/classification | [1], [2], [3] | | Assignment 2 due |
22. Nov 8 | Computer graphics: sketches | [1], [2], [3], [4], [5] | | Project proposals due (see below) |
23. Nov 10 | Computer graphics: rendering, physics | [1], [2], [3] | | |
24. Nov 15 | Computer graphics: motion capture and synthesis | [1: PDF, video], [2: PDF, video], [3: PDF, video] | | |
25. Nov 17 | Computer graphics: denoising, view interpolation, virtual reality | [1], [2], [3: PDF, video] | | |
26. Nov 22 | Computer graphics: more view prediction, materials | [1], [2] | | |
Thanksgiving: Nov 23 - 25 | | | | |
27. Nov 29 | Compression of neural networks | [1], [2], [3] | | |
28. Dec 1 | Final project presentations | | | |
29. Dec 6 | Final project presentations | | | |
30. Dec 12 | | | | Final project writeup and code due |