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blog.demofox.org | ||
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fa.bianp.net
The Langevin algorithm is a simple and powerful method to sample from a probability distribution. It's a key ingredient of some machine learning methods such as diffusion models and differentially private learning. In this post, I'll derive a simple convergence analysis of this method in the special case when the ... |
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nelari.us
In inverse transform sampling, the inverse cumulative distribution function is used to generate random numbers in a given distribution. But why does this work? And how can you use it to generate random numbers in a given distribution by drawing random numbers from any arbitrary distribution? |
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www.kuniga.me
NP-Incompleteness: |
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sander.ai
This is an addendum to my post about typicality, where I try to quantify flawed intuitions about high-dimensional distributions. |
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