Bayesian robot system identification with input and output noise

Ting, J.-A.; D’Souza, A.; Schaal, S.

doi:10.1016/j.neunet.2010.08.011

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Bayesian robot system identification with input and output noise

Ting, J.-A., D’Souza, A., & Schaal, S. (2011). Bayesian robot system identification with input and output noise. Neural Networks, 24, 99-108. doi:10.1016/j.neunet.2010.08.011.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0010-4EDD-7 Version Permalink: https://hdl.handle.net/11858/00-001M-0000-0010-4EDE-5

Genre: Journal Article

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Creators:
Ting, J.-A.¹, Author
D’Souza, A.¹, Author
Schaal, S.², Author

Affiliations:
1University of British Columbia, 201-2366 Main Mall, Vancouver, BC, Canada, V6T 1Z4; Google, Inc., Mountain View, CA 94043, United States; University of Southern California, Los Angeles, CA, 90089, United States; ATR Computational Neuroscience Laboratories, Kyoto, Japan, ou_persistent22
2Dept. Autonomous Motion, Max Planck Institute for Intelligent Systems, Max Planck Society, ou_1497646

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Free keywords: MPI für Intelligente Systeme; Abt. Schaal;

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Language(s): eng - English

Dates: Date issued: 2011

Publication Status: Issued

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Identifiers: eDoc: 590686
DOI: 10.1016/j.neunet.2010.08.011

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Title: Neural Networks

Source Genre: Journal

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Pages: - Volume / Issue: 24 Sequence Number: - Start / End Page: 99 - 108 Identifier: -