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 dfm.io
An astronomer's introduction to NumPyro | Dan Foreman-Mackey
| | austinrochford.com
R² Priors for High-Dimensional Linear Regression and Autoregressive Timeseries in PyMC | Austin Rochford
2.7 parsecs away

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| | I recently read the interesting paper The ARR2 prior: flexible predictive prior definition for Bayesian auto-regressions on the arXiv and followed its references to the also fascinating Bayesian Regre
| | erikbern.com
The hacker's guide to uncertainty estimates · Erik Bernhardsson
2.3 parsecs away

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| | I made a New Year's resolution: every plot I make during 2018 will contain uncertainty estimates. Nine months in and I have learned a lot, so I put together a summary of some of the most useful methods.
| | dsaber.com
Bayesian Regression with PyMC: A Brief Tutorial - Dan Saber
3.4 parsecs away

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| | Warning: This is a love story between a man and his Python module As I mentioned previously, one of the most powerful concepts I've really learned at Zipfian has been Bayesian inference using PyMC. PyMC is currently my favorite library of any kind in any language. I dramatically italicized "learned" because I had been taught...
| | ivyfanchiang.ca
Ivy Fan-Chiang - The Normal Distribution: A Derivation through Multi-Variable Calculus
17.1 parsecs away

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| [AI summary] The author provides a comprehensive mathematical derivation of the normal distribution using multi-variable calculus and the Herschel-Maxwell theorem.