课程名称: Probabilistic Machine Leaning - Gaussian Processes and Related Topics
授课教师:牛牧:英国格拉斯哥大学数学与统计学院
授课时间:2023年10月25日、26日、28日、30日、31日晚上20:00-21:00
授课地点: 腾讯会议:775-6338-6610
课程介绍: Gaussian processes (GPs) have gained extensive popularity in the field of machine learning due to their capacity for versatile representation and their ability to quantify uncertainty in predictions. As a pivotal Bayesian machine learning approach, GPs offer an effective means of establishing a prior distribution over the function space. This lecture series delves into the foundational principles underpinning GPs. Additionally, we will introduce the concept of sparse GPs and, time permitting, delve into Bayesian Optimization and GP latent variable models.
授课教师简介:牛牧,英国格拉斯哥大学数学与统计学院教师。主要研究方向:统计机器学习和贝叶斯统计学,在生态学、环境科学和图像处理中的应用。在《皇家统计学会杂志:B系列》和《机器学习研究杂志》发表文章多篇。