Information geometry

October 21, 2011 — December 27, 2019

functional analysis
geometry
networks
probability
score function
statistics

Suspiciously similar content

Figure 1

A placeholder for a particular type of learning on curved spaces about which I do not actually know anything.

Maybe see Azimuth’s Information Geometry Series plus the overview

1 Incoming

2 References

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Amari, Shun-ichi. 1998. “Natural Gradient Works Efficiently in Learning.” Neural Computation.
Amari, Shunʼichi. 2001. “Information Geometry on Hierarchy of Probability Distributions.” IEEE Transactions on Information Theory.
Amari, Shun-ichi, Karakida, and Oizumi. 2018. “Fisher Information and Natural Gradient Learning of Random Deep Networks.” arXiv:1808.07172 [Cond-Mat, Stat].
Amari, Shun-ichi, Park, and Fukumizu. 2000. “Adaptive Method of Realizing Natural Gradient Learning for Multilayer Perceptrons.” Neural Computation.
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———. 2002. “Probabilistic Approach to Inverse Problems.” In International Geophysics. International Handbook of Earthquake and Engineering Seismology, Part A.
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