Date | Topic | Notice | |
---|---|---|---|
Sep. | 5 | Introduction | |
7 | Deep Feedforward Network (Chapter 6) | ||
12 | Deep Feedforward Network-2 (Chapter 6) | ||
14 | Deep Feedforward Network-3 (Chapter 6) | ||
19 | Linear Factor Model (Chapter 13) | ||
21 | Linear Factor Model-2 (Chapter 13) | ||
26 | Autoencoder (Chapter 14) | ||
28 | Autoencoder-2 (Chapter 14) | ||
Oct. | 3 | Representation Learning (Chapter 15) | |
5 | Representation Learning-2 (Chapter 15) | ||
10 | Representation Learning-3 (Chapter 15) | ||
12 | Structured Probabilistic Models for Deep Learning (Chapter 16) | ||
17 | Structured Probabilistic Models for Deep Learning-2 (Chapter 16) | ||
19 | Structured Probabilistic Models for Deep Learning-3 (Chapter 16) | ||
24,26 | Midterm | ||
31 | Monte Carlo Methods (Chapter 17) | ||
Nov. | 2 | Monte Carlo Methods-2 (Chapter 17) | |
7 | Confronting the Partition Function (Chapter 18) | ||
9 | Confronting the Partition Function-2 (Chapter 18) | ||
14 | Confronting the Partition Function-3 (Chapter 18) | ||
16 | Approximate Inference (Chapter 19) | ||
21 | Approximate Inference-2 (Chapter 19) | ||
23 | Approximate Inference-3 (Chapter 19) | ||
28 | Deep Generative Models (Chapter 20) | ||
30 | Deep Generative Models-2 (Chapter 20) | ||
Dec. | 5 | Deep Generative Models-3 (Chapter 20) | |
7 | Deep Generative Models-4 (Chapter 20) | ||
12, 14 | Final |