Efficient-GP-Regression-via-Kalman-Filtering

learning

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

How to download and setup Efficient-GP-Regression-via-Kalman-Filtering

Open terminal and run command

git clone https://github.com/MarcoTodescato/Efficient-GP-Regression-via-Kalman-Filtering.git

git clone is used to create a copy or clone of Efficient-GP-Regression-via-Kalman-Filtering repositories. You pass git clone a repository URL.
it supports a few different network protocols and corresponding URL formats.

Also you may download zip file with Efficient-GP-Regression-via-Kalman-Filtering https://github.com/MarcoTodescato/Efficient-GP-Regression-via-Kalman-Filtering/archive/master.zip

Or simply clone Efficient-GP-Regression-via-Kalman-Filtering with SSH

[email protected]:MarcoTodescato/Efficient-GP-Regression-via-Kalman-Filtering.git

If you have some problems with Efficient-GP-Regression-via-Kalman-Filtering

You may open issue on Efficient-GP-Regression-via-Kalman-Filtering support forum (system) here: https://github.com/MarcoTodescato/Efficient-GP-Regression-via-Kalman-Filtering/issues

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