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CSE 4095/5095
Deep Learning
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(Tentative schedule for the course and deviations may be necessary as the course progresses.)
| Date |
Topic |
Notes |
Reading (Textbook or Other Materials) |
| Jan. 21 |
Introduction |
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Chapter 1, 2, 3, Nature review on DL, Basic calculus refresher |
| Jan. 23 |
Machine Learning Basics |
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Chapter 4, 5, Machine learning math essentials |
| Jan. 28 |
Shallow Classifiers |
Project Details |
Chapter 4, 5 |
| Jan. 30 |
Loss Functions |
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Chapter 4, 5 |
| Feb. 4 |
Optimization, SGD |
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Chapter 4, 5 |
| Feb. 11 |
Backpropagation |
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Chapter 4, 5 |
| Feb. 13 |
Intro to Neural Networks |
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| Feb. 18 |
Intro to Convolutional Neural Networks, Convolution |
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AlexNet |
| Feb. 20 |
Pooling, Demo, BP example |
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All Convolutional Net |
| Feb. 25 |
Training Neural Networks |
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| Feb. 27 |
Training Neural Networks II, Batch Normalization |
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Batch Normalization |
| Mar. 4 |
Second-order Optimization |
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Chapter 8 |
| Mar. 6 |
Regularization, Transfer Learning |
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Dropout, Blackout, DeCAF |
| Mar. 11 |
ImageNet, CNN Architectures |
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AlexNet, VGGNet, GoogleNet, ResNet |
| Mar. 13 |
CNN Architectures and Visualization |
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Wide ResNet, Zeiler and Fergus, Yosinski et al. |
| Mar. 17-21 |
No classes |
Spring Recess |
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| Mar. 25 |
Word2Vec |
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word2vec, glove, wordrank |
| Mar. 27 |
RNN |
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rnnlm |
| Apr. 1 |
LSTM, GRU |
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LSTM, GRU |
| Apr. 3 |
Image Caption, Machine Translation |
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Show, Attend and Tell, NMT with Attention |
| Apr. 8 |
Transformer |
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Attention is All You Need, The Illustrated Transformer |
| Apr. 10 |
AutoEncoder, VAE |
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VAE |
| Apr. 15 |
Generative Adversial Networks |
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GAN, DCGAN |
| Apr. 17 |
Diffusion Models |
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DDPM, Stable Diffusion |
| Apr. 22 |
Review |
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| Apr. 24 |
Presentation |
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| Apr. 29 |
Presentation |
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| May 1 |
Presentation |
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| May 8 |
Final Exam |
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| May 9 |
Project Report Due (by 11:59 pm) |
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back to course page
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