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| DESCRIPTION | This course introduces the probabilistic computing system and the related underlying knowledge. The content includes the reviewing of the basic knowledge of probability, machine learning systems based on probabilistic computing as well as related device techniques that can be leveraged in constructing the hardware probabilistic computing systems. Through the course, the students will have a refresh of the knowledge of probability, and obtain the basic knowledge of the probabilistic machine learning models such as generative models for discrete data, linear and logistic regression models based on probability directed graphical models and mixture models. On the hardware side, the students will learn how probability distributions can be efficiently generated by novel devices, which the appropriate materials and device physics. |
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| Section | Date & Time | Room | Instructor | Quota | Enrol | Avail | Wait | Remarks |
|---|---|---|---|---|---|---|---|---|
| L01 (6150) | Tu 01:30PM - 04:20PM | Rm 201, E4 | YANG, Kezhou | 20 | 19 | 1 | 0 |