The Special Math of Translating Theory to Software In Differential Eqs | Chris Rackauckas | ASE60

Поделиться
HTML-код
  • Опубликовано: 11 окт 2024

Комментарии • 9

  • @jonathandavis697
    @jonathandavis697 Год назад +4

    Awesome Chris! I'm hoping to get more of my coworkers on the Julia train but one of the first questions I always get from the grey-beards is "what are these solvers? how can I trust them and where is my ODE45." This talk is exactly what was needed!

  • @AnthonyDavid59
    @AnthonyDavid59 5 месяцев назад

    When I started looking at Julia, one of the first things that impressed me was the richness and care put into its ODE solvers. While I have yet to use them in anger, this talk gives some context to my first impressions. Thank you.

  • @vasilin97
    @vasilin97 Год назад +1

    Great talk, thank you, Chris!

  • @roboticus3647
    @roboticus3647 Год назад +5

    Good to watch, but do yourself a favor and lower the playback speed to 75% because he *talks so, so fast*.

  • @sucim
    @sucim 6 месяцев назад

    So good! Would be nice if you would spend like 30s to explain what e.g. stiff means (for noobs like me) but otherwise it was a really nice presentation. I was in the rk4 and chill camp but now I‘m higher order curious

    • @aaronkaw4857
      @aaronkaw4857 6 месяцев назад

      Stiffness is when your ode solver needs a really small stepsize, otherwise it's unstable.

    • @sucim
      @sucim 6 месяцев назад +1

      @@aaronkaw4857 Interesting! That makes it sound like a quantitative property (blurred lines on what constitutes a "small stepsize"). From the name it always appeared to be a qualitative differrence between systems 🤔

  • @aaronkaw4857
    @aaronkaw4857 6 месяцев назад

    I hope Tsitouris sees this presentation, or at least knows his paper is being applied.

  • @standard_output
    @standard_output 3 дня назад

    he has very high blood pressure 😅