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DeepKriging: Spatially Dependent Deep Neural Networks for Spatial Prediction

By Yuxiao Li and others
In spatial statistics, a common objective is to predict the values of a spatial process at unobserved locations by exploiting spatial dependence. In geostatistics, Kriging provides the best linear unbiased predictor using covariance functions and is often associated with Gaussian processes. However, when considering non-linear prediction for non-Gaussian and categorical... Show more
July 25, 2020
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DeepKriging: Spatially Dependent Deep Neural Networks for Spatial Prediction
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