Efficient-GP-Regression-via-Kalman-Filtering

Code to implement efficient spatio-temporal Gaussian Process regression via iterative Kalman Filtering. KF is used to resolve the temporal part of the space-time process while, standard GP regression is used for the spatial part

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39 Stars

12 Forks

39 Watchers

Matlab Language

gpl-3.0 License

100 SrcLog Score

Cost to Build

$134.7K

Market Value

$184.5K

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Growth over time

8 data points · 2021-08-01 → 2026-04-01

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What is the MarcoTodescato/Efficient-GP-Regression-via-Kalman-Filtering GitHub project? Description: "Code to implement efficient spatio-temporal Gaussian Process regression via iterative Kalman Filtering. KF is used to resolve the temporal part of the space-time process while, standard GP regression is used for the spatial part". Written in Matlab. Explain what it does, its main use cases, key features, and who would benefit from using it.

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