Inference for Continuous Stochastic Processes Using Gaussian Process Regression
Gaussian process regression (GPR) is a long-standing technique for statistical interpolation between observed data points. Having originally been applied to spatial analysis in the 1950s, GPR offers highly nonlinear predictions with uncertainty adjusting to the degree of extrapolation -- at the expe...
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| Language: | en |
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2014
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| Online Access: | http://hdl.handle.net/10012/8159 |