Sequential Gaussian Processes for Online Learning of Nonstationary Functions-Reference-Cited by-同舟云学术

Sequential Gaussian Processes for Online Learning of Nonstationary Functions

Author:

Zhang Michael Minyi¹^ORCID,Dumitrascu Bianca²,Williamson Sinead A.³,Engelhardt Barbara E.⁴

Affiliation:

1. Department of Statistics and Actuarial Science, University of Hong Kong, Hong Kong, SAR, China

2. Department of Statistics and Herbert and Florence Institute for Cancer Dynamics, Columbia University, New York, NY, USA

3. Department of Statistics and Data Science, The University of Texas at Austin, Austin, TX, USA

4. Department of Biomedical Data Science, Stanford University, Stanford, CA, USA

Funder

HKU-URC Seed Fund for Basic Research for New Staff

HKU Libraries Open Access Author Fund

HKU Libraries

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Signal Processing

Link

Reference55 articles.

2. Variational mixture of Gaussian process experts;yuan;Proc Adv Neural Inf Process Syst,0

3. Deep structured mixtures of Gaussian processes;trapp;Proc Int Conf Artif Intell Statist,0

4. Fast allocation of Gaussian process experts;nguyen;Proc Int Conf Mach Learn,0

5. Learning to detect sepsis with a multitask Gaussian process RNN classifier;futoma;Proc Int Conf Mach Learn,0

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