# Stochastic processes on manifolds

March 1, 2021 — March 1, 2021

Gaussian

geometry

Hilbert space

how do science

kernel tricks

machine learning

PDEs

physics

regression

signal processing

spatial

statistics

stochastic processes

time series

uncertainty

TBD.

## 1 References

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Bhattacharya, and Bhattacharya. 2012.

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Borovitskiy, Terenin, Mostowsky, et al. 2020. “Matérn Gaussian Processes on Riemannian Manifolds.”

*arXiv:2006.10160 [Cs, Stat]*.
Calandra, Peters, Rasmussen, et al. 2016. “Manifold Gaussian Processes for Regression.” In

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Chikuse, and 筑瀬. 2003.

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*Conference on Learning Theory*.
Lindgren, Rue, and Lindström. 2011. “An Explicit Link Between Gaussian Fields and Gaussian Markov Random Fields: The Stochastic Partial Differential Equation Approach.”

*Journal of the Royal Statistical Society: Series B (Statistical Methodology)*.
Manton. 2013. “A Primer on Stochastic Differential Geometry for Signal Processing.”

*IEEE Journal of Selected Topics in Signal Processing*.
Yaglom. 1961. “Second-Order Homogeneous Random Fields.”

*Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability, Volume 2: Contributions to Probability Theory*.