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#markov-chains — Public Fediverse posts

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  1. Beginner #MarkovChains question:
    I'm working on a small analysis program for a friend. It's already existing code where you select a number of labels from a labelled sequence of interactions and then supposedly get a transition matrix from them.

    BUT - the code ignores intermediate labels when counting transitions.
    e.g. if a sequence has three labelled members w,x,y, and you only want to analyse w, and y, the current code would count that as a transition from w to y, ignoring the intervening x.

    This does not seem appropriate for calculating transition probabilities. If I understand correctly, this should not be counted at all, since the transition was w -x, then x-y.

    Does that sound like I have understood correctly?

  2. 🚨 BREAKING: High school essay from 2012 declares *Markov Chains* as the OG language models! 🙄 Apparently, *Linear Algebra 101* had all the answers before #AI got cool. Who knew teenage musings could redefine the hype cycle? 😂
    elijahpotter.dev/articles/mark #MarkovChains #LinearAlgebra #HypeCycle #TeenageMusings #HackerNews #ngated

  3. 🎉 Mégra 0.0.16 is out! Just some small improvements I found while preparing for a workshop.

    Thanks @alice_ahora for improving the tutorial with me!

    github.com/the-drunk-coder/meg

    megra-doc.readthedocs.io/en/la

    :megra_wavetable:

    #livecoding #markovchains #rust

  4. Teaching ChatGPT-4o is a great way to learn.

    It's always nice to notice you know something ChatGPT doesn't know, as it typically means you know something most specialists in the field don't know:
    chatgpt.com/share/67ac8053-bcf

    #LLM #mathematics #MarkovChains #MDPs

  5. So the results are fun to browse, but sometimes a bit too nonsensical.

    Anyone experienced with #MarkovChains able to share any tips on how to make the output better?

    #CreativeCoding #GenerativeText

  6. CW: Job ad (postdoc)

    Come to the University of Leeds and work as a postdoc for 2.5 years with my colleague Jon Ward on his project to develop ‘lumping’ techniques to approximate Markov chain dynamics on networks. Deadline for applications is 15 November. More details: jobs.leeds.ac.uk/Vacancy.aspx?

    #NetworkScience #DynamicalSystems #StatisticalMechanics #MarkovChains #job #postdoc