Modulating scalable Gaussian processes for expressive statistical learning

• Main Authors: Liu, Haitao, Ong, Yew-Soon, Jiang, Xiaomo, Wang, Xiaofang
• 其他作者: School of Computer Science and Engineering
• 格式: Article
• 語言: English
• 出版: 2022
• 主題: Engineering::Computer science and engineering; Gaussian Process; Modulation
• 在線閱讀: https://hdl.handle.net/10356/162582
• 機構: Nanyang Technological University

For a learning task, Gaussian process (GP) is interested in learning the statistical relationship between inputs and outputs, since it offers not only the prediction mean but also the associated variability. The vanilla GP however is hard to learn complicated distribution with the property of, e.g.,...