Code for Multi-Output Gaussian Process Regression and Learning Approaches

software

posted on 2019-01-09, 12:04 authored by Le YangLe Yang, Ke WangKe Wang, Lyudmila MihaylovaLyudmila Mihaylova

This is the implementation of the approaches developed in this work.

L. Yang, K. Wang and L. S. Mihaylova, "Online Sparse Multi-Output Gaussian Process Regression and Learning," in IEEE Transactions on Signal and Information Processing over Networks. doi: 10.1109/TSIPN.2018.2885925

Apart from the code, data for validation of the approaches are also provided.

Funding

CSC grants

History

References

http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8571257&isnumber=7103030

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Department of Automatic Control and Systems Engineering

Keywords

Multi-output Gaussian Processes Sparse data online regression and learning marginalized particle filter Kullback-Leibler divergence Control Systems, Robotics and Automation Computer Engineering

Licence

MIT