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Stationary Kernels and Gaussian Processes on Lie Groups and their Homogeneous Spaces I: the Compact Case. (arXiv:2208.14960v1 [stat.ME])
Sept. 1, 2022, 1:10 a.m. | Iskander Azangulov, Andrei Smolensky, Alexander Terenin, Viacheslav Borovitskiy
cs.LG updates on arXiv.org arxiv.org
Gaussian processes are arguably the most important model class in spatial
statistics. They encode prior information about the modeled function and can be
used for exact or approximate Bayesian inference. In many applications,
particularly in physical sciences and engineering, but also in areas such as
geostatistics and neuroscience, invariance to symmetries is one of the most
fundamental forms of prior information one can consider. The invariance of a
Gaussian process' covariance to such symmetries gives rise to the most natural …
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