Variational Inference for Uncertainty on the Inputs of Gaussian Process Models

Andreas DamianouMichalis K. TitsiasNeil D. Lawrence
, 2014.

Abstract

Cite this Paper


BibTeX
@InProceedings{pmlr-v-damianou-variational14, title = {Variational Inference for Uncertainty on the Inputs of Gaussian Process Models}, author = {Andreas Damianou and Michalis K. Titsias and Neil D. Lawrence}, year = {}, editor = {}, url = {http://inverseprobability.com/publications/damianou-variational14.html}, abstract = {} }
Endnote
%0 Conference Paper %T Variational Inference for Uncertainty on the Inputs of Gaussian Process Models %A Andreas Damianou %A Michalis K. Titsias %A Neil D. Lawrence %B %C Proceedings of Machine Learning Research %D %E %F pmlr-v-damianou-variational14 %I PMLR %J Proceedings of Machine Learning Research %P -- %U http://inverseprobability.com %V %W PMLR %X
RIS
TY - CPAPER TI - Variational Inference for Uncertainty on the Inputs of Gaussian Process Models AU - Andreas Damianou AU - Michalis K. Titsias AU - Neil D. Lawrence BT - PY - DA - ED - ID - pmlr-v-damianou-variational14 PB - PMLR SP - DP - PMLR EP - L1 - UR - http://inverseprobability.com/publications/damianou-variational14.html AB - ER -
APA
Damianou, A., Titsias, M.K. & Lawrence, N.D.. (). Variational Inference for Uncertainty on the Inputs of Gaussian Process Models. , in PMLR :-

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