Neural Controlled Differential Equations for Irregular Time Series

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  • Опубліковано 6 жов 2024

КОМЕНТАРІ • 9

  • @farouk-hjabo
    @farouk-hjabo 3 роки тому +5

    Absolutely phenomenal!
    The work you are doing is amazing.
    Smooth presentations, readable understandable papers, and open source code.
    Thank you so much your work is closely related to my thesis.
    Keep up the good work, I wish you all the best.

  • @Hannah-cb7wr
    @Hannah-cb7wr 4 роки тому +3

    Very interesting! And thanks for publishing the code, sadly not the standard for ML research.

    • @patrickkidger1285
      @patrickkidger1285  4 роки тому +4

      Thankyou! I think publishing code is becoming more frequent these days, thankfully.

  • @jaimecascantevega1123
    @jaimecascantevega1123 3 роки тому +1

    This is awesome! Could you please provide any insight on how to include estimates of time-varying parameters?

  • @yuhangguo2409
    @yuhangguo2409 4 роки тому

    Nice talk! BTW, where can I download the slides? Thx!

    • @patrickkidger1285
      @patrickkidger1285  4 роки тому +1

      A version of these slides are available here: kidger.site/links/CZszzuRmMmzo

  • @loo5405
    @loo5405 4 роки тому

    could you please release a model/.py for forecasting?

    • @patrickkidger1285
      @patrickkidger1285  4 роки тому +1

      We have a GitHub repo (and example) at github.com/patrick-kidger/NeuralCDE you can check out.
      We didn't specifically consider a forecasting problem in the paper but it should be straightforward to set up, using the classification example as a guide.

    • @loo5405
      @loo5405 4 роки тому +1

      @@patrickkidger1285 nice, ill give a try, im new to neural ode and im currently learning how to solve/train in julia, checking the benchmark it should be also faster than pytorch, so i wonder why cde and other models like latent ode aren't done in julia. sorry my english.