Adaptive Design of Experiments Based on Gaussian Processes

  • Evgeny Burnaev
  • Maxim PanovEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9047)


We consider a problem of adaptive design of experiments for Gaussian process regression. We introduce a Bayesian framework, which provides theoretical justification for some well-know heuristic criteria from the literature and also gives an opportunity to derive some new criteria. We also perform testing of methods in question on a big set of multidimensional functions.


Active learning Computer experiments Sequential design Gaussian processes 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Institute for Information Transmission ProblemsMoscowRussia
  2. 2.DATADVANCE, LLCMoscowRussia
  3. 3.PreMoLabMIPTDolgoprudnyRussia

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