深度生成模型
Deep Generative Models
| 節 | 週三 |
|---|---|
2 09:00–09:50 | 深度生成模型 CM216（歸仁） 3 節連堂 |
3 10:10–11:00 | |
4 11:10–12:00 |
* 根據陽明交大上課時間表所列
Generative models are a method in AI and machine learning that are widely used in various fields, in particular, generative AI such as large language models. They can serve as a foundational approach, used in conjunction with other algorithms, for example, as part of data augmentation, or they can simply be used to generate more content. In recent years, there have been many advances in generative models due to the development of deep learning, such as Diffusion models, GANs, VAEs, autoregression models, Generative flow, and so on. In this course, we will start with an introduction to these foundational models and then proceed to cover some of the latest developments.
Deep learning, linear algebra
無備註
online video and bi-weekly homework
homework 100%
教師未提供此項資料
| 週次 | 主題 |
|---|---|
| 第 1 週 | Introduction 2025-02-19(三) |
| 第 2 週 | Introduction: Autoencoder 2025-02-26(三) |
| 第 3 週 | Introduction: Autoregressive model 2025-03-05(三) |
| 第 4 週 | Introduction: n-gram and language generalization 2025-03-12(三) |
| 第 5 週 | VAE: Variational Autoencoder 2025-03-19(三) |
| 第 6 週 | GAN: GAN, DCGAN and math 2025-03-26(三) |
| 第 7 週 | GAN: WGAN and SNGAN 2025-04-02(三) |
| 第 8 週 | Conditional GAN 2025-04-09(三) |
| 第 9 週 | Pix2Pix and CycleGAN 2025-04-16(三) |
| 第 10 週 | Diffusion Model, Generative Flow 2025-04-23(三) |
| 第 11 週 | Diffusion Model. Theory and Stochastic Differential Equation 2025-04-30(三) |
| 第 12 週 | Diffusion Model and Language Model 2025-05-07(三) |
| 第 13 週 | Generative Language models: Applications and Theory 2025-05-14(三) |
| 第 14 週 | Generative Language models: Implementations 2025-05-21(三) |
| 第 15 週 | Recent advances 2025-05-28(三) |
| 第 16 週 | Summary and review 2025-06-04(三) |
online
- 地點
- 教師未提供此項資料
- 時間
- 教師未提供此項資料
- 聯絡方式
- 教師未提供此項資料