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City Palaiseau / Aires et / New York / Paris / / Company Amazon / / Country United States / / Facility Columbia University/NASA Goddard Institute / France W. B. Rossow NASA Goddard Institute / / IndustryTerm real-world applications / subsequent algorithm / nonoptimum learning algorithm / uncertainty tools / neural network / actual solution / neural networks / satellite colocations / emitted and reflected energy / neural network inversion algorithm / learning algorithm / / MusicAlbum Monte Carlo / / Organization Observatoire de Paris / American Geophysical Union / Columbia University / F. Aires Department of Applied Physics and Applied Mathematics / France W. B. Rossow NASA Goddard Institute for Space Studies / National Aeronautics and Space Administration / Institute for Space Studies / / Person Ain Ey / Ain Ain / Ain ðt / / Position Bishop / General / / ProgrammingLanguage L / / ProvinceOrState West Virginia / Mississippi / New York / / PublishedMedium JOURNAL OF GEOPHYSICAL RESEARCH / / Technology Geophysics / learning algorithm / radiation / remote sensing / Neural network / neural network inversion algorithm / microwave / simulation / subsequent algorithm / nonoptimum learning algorithm / PDF / / SocialTag 
JOURNAL OF GEOPHYSICAL RESEARCH, VOL. 109, D10304, doi:2003JD004174, 2004 Neural network uncertainty assessment using Bayesian statistics with application to remote sensing: 2. Output errors F. Aires