学术报告：Introduction to Bayesian Networks and Inference

学术报告：Introduction to Bayesian Networks and Inference

报告题目：Introduction to Bayesian Networks and Inference

报告人：加拿大Alberta大学，Biao Huang教授

报告时间：2021年11月19日（周五）10:00-11:00

报告地点：崂山校区william威廉亚洲官方楼（D1楼）410

主办单位：自动化与电子工程学院

报告简介：Bayesian theory, due to its mathematical rigor and application flexibility, has attracted great interests from both academic researchers and industrial practitioners. The original Bayesian theory, as a single formula, can evolve into pages of long mathematical derivations. Yet the result provides very meaningful solutions to the practical problems. Bayesian inference has long application history in control engineering. The most well-known application of Bayesian theory is Kalman filter which has been widely adopted in control engineering applications. It is now commonly recognized that many practical problems may be formulated mathematically under Bayesian framework and readily solved. Bayesian inference is getting even more popular due to the growing interest in Data Science. This presentation will give a historical overview of Bayesian theory and introduction to its network architecture and inference.