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AnimaAnandkumar's profile
Prof. Anima Anandkumar
Prof. Anima Anandkumar
Prof. Anima Anandkumar
@AnimaAnandkumar

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Prof. Anima Anandkumar

@AnimaAnandkumar

Director of #AI #research @nvidia, Bren #Professor @Caltech, Fmr Principal scientist @awscloud #Sloan fellow #Tensors Erdos #2 #dancer http://anima-ai.org 

Santa Clara, CA
tensorlab.cms.caltech.edu/users/anima/
Joined October 2014

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    1. Nando de Freitas‏ @NandoDF Sep 23
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      Brain-inspired variant of memory replayhttps://flip.it/Hu8rt2 

      3 replies 13 retweets 57 likes
    2. Prof. Anima Anandkumar‏ @AnimaAnandkumar Sep 24
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      Replying to @NandoDF

      Our recent work builds recurrent feedback into any feed forward #NeuralNetworks by posing feedback as a generative model that aims to reconstruct lower level features https://arxiv.org/abs/2007.09200  @YujiaHuangC @JamesGornet @TanNguyen689 @ZhidingYu @doristsao @Caltech @NVIDIAAI

      1 reply 5 retweets 25 likes
    3. Filip Piekniewski‏ @filippie509 Sep 24
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      Replying to @AnimaAnandkumar @NandoDF and

      If you haven't yet, you should really take a look at our 2016 Predictive Vision Model paper: https://arxiv.org/abs/1607.06854 

      2 replies 0 retweets 0 likes
    4. Rebel Science‏ @RebelScience Sep 27
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      Replying to @filippie509 @AnimaAnandkumar and

      I just now read the abstract. Interesting. Can your approach handle this problem? A child that has learned to read black text on a white background can instantly recognize white text on a black background. Can your model handle this problem or would it need additional training?

      1 reply 0 retweets 0 likes
    5. Rebel Science‏ @RebelScience Sep 27
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      Replying to @RebelScience @filippie509 and

      OK. Your tracker needs some kind of supervision. Sorry, that won't solve universal perception. The brain can instantly tract any object in 3D even if it has never seen it before. Universality is essential. That's the difference between general and non-general intelligence.

      1 reply 0 retweets 0 likes
    6. Rebel Science‏ @RebelScience Sep 27
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      Replying to @RebelScience @filippie509 and

      * track

      1 reply 0 retweets 0 likes
    7. Filip Piekniewski‏ @filippie509 Sep 27
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      Replying to @RebelScience @AnimaAnandkumar and

      I'm not saying this paper solves general perception. It's a small step, an outline of a more general approach in which hierarchy of features is developed in a different manner than a regular neocognitron-clone deep net. Neocognitron is a dead end, as many will soon realize.

      2 replies 0 retweets 0 likes
      Prof. Anima Anandkumar‏ @AnimaAnandkumar Sep 27
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      Replying to @filippie509 @RebelScience and

      I have been blocked. So I can't view what this discussion is about

      8:04 PM - 27 Sep 2020
      1 reply 0 retweets 0 likes
        1. New conversation
        1. Filip Piekniewski‏ @filippie509 Sep 27
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          Replying to @AnimaAnandkumar @RebelScience and

          The gentleman took an issue with the fact that we use unsupervised, predictive features to supervise-train an object tracker. I'd love to have everything unsupervised, but in reality I think there will be a need to supervise readouts from such systems for quite some time.

          1 reply 0 retweets 1 like
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