8 Matching Annotations
1. Jun 2022
2. www.kryakin.site www.kryakin.site
1. (1.5)Proposition.

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3. Feb 2022
4. www.tmpl.fi www.tmpl.fi

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5. Jan 2022
6. eductive.ca eductive.ca
1. Une distribution gaussienne pour les notes des étudiants n’est pas un indicateur de rigueur.

Curving grades remains an unquestioned practice, in some contexts. Despite all the debunking which has been done since Terman's (in)famous work...

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7. Jun 2020
1. Liu, Andrew, and Mason A. Porter. ‘Spatial Strength Centrality and the Effect of Spatial Embeddings on Network Architecture’. Physical Review E 101, no. 6 (9 June 2020): 062305. https://doi.org/10.1103/PhysRevE.101.062305.

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9. May 2020
10. statmodeling.stat.columbia.edu statmodeling.stat.columbia.edu
1. Statistical Modeling, Causal Inference, and Social Science. (2020 April 22). Blog Post: New analysis of excess coronavirus mortality; also a question about poststratification. https://statmodeling.stat.columbia.edu/2020/04/22/analysis-of-excess-coronavirus-mortality-also-a-question-about-poststratification/

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11. Sep 2018
12. docs.pymc.io docs.pymc.io
1. conditional distribution for individual components can be constructed

So the conditional distribution is conditioned on other components?

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13. am207.github.io am207.github.io
1. calculation once again involves inverting a NxN matrix as in the kernel space representation of regression

this is why we use MCMC or other distribution sampling technique instead

2. in equation B for the marginal of a gaussian, only the covariance of the block of the matrix involving the unmarginalized dimensions matters! Thus “if you ask only for the properties of the function (you are fitting to the data) at a finite number of points, then inference in the Gaussian process will give you the same answer if you ignore the infinitely many other points, as if you would have taken them all into account!”(Rasmunnsen)

key insight into Gaussian processes