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Estimating the distribution of Galaxy Morphologies on a continuous space
Published online by Cambridge University Press: 01 July 2015
Abstract
The incredible variety of galaxy shapes cannot be summarized by human defined discrete classes of shapes without causing a possibly large loss of information. Dictionary learning and sparse coding allow us to reduce the high dimensional space of shapes into a manageable low dimensional continuous vector space. Statistical inference can be done in the reduced space via probability distribution estimation and manifold estimation.
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- Contributed Papers
- Information
- Proceedings of the International Astronomical Union , Volume 10 , Symposium S306: Statistical Challenges in 21st Century Cosmology , May 2014 , pp. 68 - 71
- Copyright
- Copyright © International Astronomical Union 2015
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