Bayesian Networks: Inference using Variable Elimination

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  • Опубликовано: 8 ноя 2024

Комментарии • 19

  • @towers3372
    @towers3372 9 месяцев назад +5

    I love this video, it's much better than the mechanical approach to Variable Elimination. Now I understand WHY it works, and it is so much easier to remember!

  • @ConorJurewicz
    @ConorJurewicz 9 дней назад

    Beautiful explanation, great job!

  • @Sergeak21
    @Sergeak21 Год назад +10

    i wish you the very best,
    with all the love
    - a struggling student

  • @ashwinkashyap8665
    @ashwinkashyap8665 7 месяцев назад

    Excellent explanation professor!

  • @aisha3540
    @aisha3540 2 года назад +11

    very helpful explanation! i wish my professor explained it this well :)

  • @suryakanth5370
    @suryakanth5370 2 года назад +6

    This is what should be captioned as watch till end

  • @shikharpandya4927
    @shikharpandya4927 6 месяцев назад +3

    Thanks a lot IIT D

  • @BAMEADManiyar
    @BAMEADManiyar 4 месяца назад

    I dont understand pushing the Summation, I know when constant we can push but here I cant identify which is constant. And moreover I believe that they are the distribution. Containg 2,4 values not only single value. Correct me if im wrong.

  • @gijsvermeulen8235
    @gijsvermeulen8235 9 месяцев назад

    Love the intro

  • @raihanulbaritanvir3845
    @raihanulbaritanvir3845 4 года назад +1

    awesome lecture

  • @akash1927
    @akash1927 3 года назад +4

    I don't understand how that full joint distribution summing over hidden variable came. EE Dept.

    • @kpb6
      @kpb6 3 года назад +9

      @Akash We have assumed that Earthquake and Burglary are two independent events and they influence Alarm. Hence P(B) and P(E) are multiplied as they are. But alarm ringing depends on E and B hence P(A|,E.B). Since alarm influences John calling or Mary calling, we have P(j|A) and P(m|A). Hence P(B) P(E) P(A|E,B) P(m|A) P(j|A)

    • @manjunathakapilsharma
      @manjunathakapilsharma 3 года назад +1

      @@kpb6 I have one more doubt , what if we have some more parents to earthquake and burglary and some more child nodes to john and mary ?? Do all these things should be considered as hidden variables for computations?

    • @joebashour
      @joebashour 3 года назад +2

      ​@@manjunathakapilsharma Precisely.
      For instance:
      if [Earthquake] had 2 causal nodes (i.e. parents), then we would do P(E | parents) etc.

    • @9181shreyasbhatt
      @9181shreyasbhatt 9 месяцев назад

      If u can mention the particular timestamp, we might be able to exactly clarify the doubt.

    • @shreerambhat1442
      @shreerambhat1442 9 месяцев назад

      tq so much 😇@@kpb6

  • @jpatel2002
    @jpatel2002 3 месяца назад

    21:48 i think its because p(bug...)= 0.001 and p(earth...) = 0.002

  • @VSSRaviTejaDendukuri
    @VSSRaviTejaDendukuri 5 месяцев назад

    From 14:00 How was sum over E written as f1(A,B) and sum over B written as f2(A)?

  • @nealpobrien
    @nealpobrien 6 месяцев назад

    Good lecture, but he expects students to guess what he's about to say often without it yet being clear what he's looking for, which seems common in teaching probability.