Nonstationary Covariance Functions for Gaussian Process Regression

Nonstationary Covariance Functions for Gaussian Process Regression (2004)

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by Christopher J. Paciorek , Mark J. Schervish

Venue:	In Proc. of the Conf. on Neural Information Processing Systems (NIPS
Citations:	25 - 2 self

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@INPROCEEDINGS{Paciorek04nonstationarycovariance,
    author = {Christopher J. Paciorek and Mark J. Schervish},
    title = {Nonstationary Covariance Functions for Gaussian Process Regression},
    booktitle = {In Proc. of the Conf. on Neural Information Processing Systems (NIPS},
    year = {2004},
    publisher = {MIT Press}
}

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Abstract

We introduce a class of nonstationary covariance functions for Gaussian process (GP) regression. Nonstationary covariance functions allow the model to adapt to functions whose smoothness varies with the inputs.

Citations

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