Description:

Our GP-grid algorithm uses the multiplicative structure of most common kernels to reduce runtime complexity from O(N^3) to O(D*N^((D+1)/D), where D is the number of dimensions. Importantly, our GP-grid algorithm is exact, requiring no approximations or sparsification procedures to perform inference.

We generalize GP-grid to handle incomplete grids and heteroscedastic noise, which importantly enables GP-grid to naturally incorporate known statistical properties of the data.

Changes to previous version:

Initial Announcement on mloss.org.

BibTeX Entry: Download

Supported Operating Systems: Windows, Unix, Mac

Data Formats: Any Format Supported By Matlab

Tags: Kernel, Gaussian Processes, Multidimensional

Archive: download here

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