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H. Paul Keeler

H. Paul Keeler

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H. Paul Keeler

Month: January 2023

New link – math3ma.com

In my internet wanderings, I stumbled upon this blog:

https://almostsuremath.com/

The writer, Tae-Danae Bradley, wrote a PhD applying category theory (a field of mathematics that strives for abstraction) to problems in machine learning.

Author Paul KeelerPosted on January 4, 2023January 29, 2025Categories New linkTags category theory, machine learningLeave a comment on New link – math3ma.com

About

Paul Keeler works in applied probability, applied statistics, telecommunications, random networks, and  machine learning coupled with randomness (or generative artificial intelligence).

GitHub. Google Scholar.

Recent Posts

  • The return of the Box-Muller method due to GPUs
  • Determinantal learning for selecting subsets in wireless networks
  • Learning Theory from First Principles
  • Lecture slides based on Baccelli, Błaszczyszyn, and Karray
  • The Metropolis-Hastings algorithm in C with multi-variable densities

Popular posts

  • Simulating Poisson random variables – Direct method
  • Simulating a homogeneous Poisson point process on a…
  • Voronoi tessellations
  • Simulating an inhomogeneous Poisson point process
  • Wiener or Brownian (motion) process
  • Thinning point processes
  • Stochastic processes
  • Signal-to-interference ratio in wireless networks
  • Simulating a Matérn cluster point process
  • Simulating a Poisson point process on a disk

Other websites

  • Gregory Gundersen
  • Almost Sure
  • Count Bayesie
  • Almost Sure
  • Math3ma
  • Andrew Gelman
  • Connor Johnson
  • Eventually Almost Everywhere
  • Extreme Learning
  • GitHub - hpaulkeeler
  • Mad (Data) Scientist
  • Pensées Libres
  • Structured Procrastination
  • ThatsMaths
  • Xi'an's Og

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