GPR works well with small datasets and generates a metric of confidence of a predicted result, but it's moderately complex and the results are not easily interpretable, says Dr. James McCaffrey of ...

Gaussian process regression is a sophisticated technique that uses what is called the kernel trick to deal with complex non-linear data, and L2 regularization to avoid model overfitting where a model ...

Pantelis Samartsidis, Claudia R. Eickhoff, Simon B. Eickhoff, Tor D. Wager, Lisa Feldman Barrett, Shir Atzil, Timothy D. Johnson, Thomas E. Nichols Journal of the Royal Statistical Society. Series C ...