It is all in the noise: Efficient multi-task Gaussian process inference with 
structured residuals

Rakitsch, Barbara; Lippert, Christoph; Borgwardt, Karsten M.; Stegle, Oliver

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It is all in the noise: Efficient multi-task Gaussian process inference with structured residuals

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Rakitsch, Barbara
Research Group Machine Learning and Computational Biology, Max Planck Institute for Intelligent Systems, Max Planck Society;

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Borgwardt, Karsten M.
Research Group Machine Learning and Computational Biology, Max Planck Institute for Intelligent Systems, Max Planck Society;

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Rakitsch, B., Lippert, C., Borgwardt, K. M., & Stegle, O. (2013). It is all in the noise: Efficient multi-task Gaussian process inference with structured residuals. In C. Burges, L. Bottou, M. Welling, Z. Ghahramani, & K. Weinberger (Eds.), Advances in Neural Information Processing Systems 26 (NIPS 2013) (pp. 1466-1474). Retrieved from http://papers.nips.cc/paper/5089-it-is-all-in-the-noise-efficient-multi-task-gaussian-process-inference-with-structured-residuals.

Cite as: https://hdl.handle.net/11858/00-001M-0000-0015-3A26-A

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