• Corpus ID: 239016048

Multi-group Gaussian Processes

@inproceedings{Li2021MultigroupGP,
  title={Multi-group Gaussian Processes},
  author={Didong Li and Andrew Jones and Sudipto Banerjee and Barbara E. Engelhardt},
  year={2021}
}
Gaussian processes (GPs) are pervasive in functional data analysis, machine learning, and spatial statistics for modeling complex dependencies. Modern scientific data sets are typically heterogeneous and often contain multiple known discrete subgroups of samples. For example, in genomics applications samples may be grouped according to tissue type or drug exposure. In the modeling process it is desirable to leverage the similarity among groups while accounting for differences between them… 

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