Prediction at an Uncertain Input for Gaussian Processes and Relevance Vector 
Machines - Application to Multiple-Step Ahead Time-Series Forecasting

Quiñonero-Candela, J; Girard, A; Rasmussen, CE

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Prediction at an Uncertain Input for Gaussian Processes and Relevance Vector Machines - Application to Multiple-Step Ahead Time-Series Forecasting

Quiñonero-Candela, J., Girard, A., & Rasmussen, C.(2003). Prediction at an Uncertain Input for Gaussian Processes and Relevance Vector Machines - Application to Multiple-Step Ahead Time-Series Forecasting (IMM-2003-18).

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-DDF6-7 Version Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-DDF7-5

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Creators:
Quiñonero-Candela, J¹, Author
Girard, A, Author
Rasmussen, CE¹, Author

Affiliations:
1Department Empirical Inference, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497795

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Dates: Date issued: 2003

Publication Status: Issued

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Identifiers: Report Nr.: IMM-2003-18
BibTex Citekey: 2578

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