1. What have the authors contributed in "Extending gaussian process emulation using cluster analysis and artificial neural networks to fit big training sets" ?
The authors show how Gaussian process emulation can be extended to handle large training sets by first dividing the training set into smaller subsets using cluster analysis, then training an emulator for each subset, and finally combining the emulators using an artificial neural network.. The authors furthermore compare the performance of multiple artificial neural network configurations with varying training parameters.
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