Bayesian Networks: Inference using Variable Elimination

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  • Опубліковано 15 гру 2024

КОМЕНТАРІ • 21

  • @towers3372
    @towers3372 10 місяців тому +9

    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!

  • @Sergeak21
    @Sergeak21 Рік тому +14

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

  • @SarabjotColabFiles
    @SarabjotColabFiles 5 днів тому

    The best explanation on the internet

  • @ashwinkashyap8665
    @ashwinkashyap8665 8 місяців тому +1

    Excellent explanation professor!

  • @aisha3540
    @aisha3540 3 роки тому +12

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

  • @ConorJurewicz
    @ConorJurewicz Місяць тому +1

    Beautiful explanation, great job!

  • @EXslowedreverbed
    @EXslowedreverbed 2 дні тому

    literally today i didn,t learn any thing from this lecture hope the students seating there in front of him have the same situation , i noticed it during the lecture.

  • @suryakanth5370
    @suryakanth5370 2 роки тому +7

    This is what should be captioned as watch till end

  • @VSSRaviTejaDendukuri
    @VSSRaviTejaDendukuri 7 місяців тому +1

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

  • @shikharpandya4927
    @shikharpandya4927 7 місяців тому +4

    Thanks a lot IIT D

  • @raihanulbaritanvir3845
    @raihanulbaritanvir3845 4 роки тому +2

    awesome lecture

  • @BAMEADManiyar
    @BAMEADManiyar 5 місяців тому +1

    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.

  • @jpatel2002
    @jpatel2002 5 місяців тому +1

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

  • @gijsvermeulen8235
    @gijsvermeulen8235 10 місяців тому +1

    Love the intro

  • @akash1927
    @akash1927 3 роки тому +5

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

    • @kpb6
      @kpb6 3 роки тому +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 роки тому +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 роки тому +2

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

    • @9181shreyasbhatt
      @9181shreyasbhatt 10 місяців тому

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

    • @shreerambhat1442
      @shreerambhat1442 10 місяців тому

      tq so much 😇@@kpb6

  • @nealpobrien
    @nealpobrien 7 місяців тому +1

    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.