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Poster

Nonstationary Gaussian Process Regression using a Latent Extension of the Input Space

MPS-Authors
/persons/resource/persons84138

Pfingsten,  T
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons84030

Kuss,  M
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

/persons/resource/persons84156

Rasmussen,  CE
Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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ISBA-2006.pdf
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Citation

Pfingsten, T., Kuss, M., & Rasmussen, C. (2006). Nonstationary Gaussian Process Regression using a Latent Extension of the Input Space. Poster presented at Eighth World Meeting of the International Society for Bayesian Analysis (ISBA 2006), Benidorm, Spain.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0013-D2F9-A
Abstract
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