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avibryant's profile
Avi Bryant
Avi Bryant
Avi Bryant
@avibryant

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Avi Bryant

@avibryant

Happiest when working on Random Forests from random beaches.

Galiano Island
avibryant.com
Joined November 2006

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    1. Avi Bryant‏ @avibryant May 19

      I'm super excited by how close we're getting to releasing some work I've been doing at Stripe on a static compute graph + bayesian inference library for Scala. Depending on your background, you might think of it as aspiring to be "TensorFlow for small data" or "Stan on the JVM".

      2 replies 7 retweets 111 likes
      Show this thread
      Avi Bryant‏ @avibryant May 19

      If anyone's interested in getting early access to the repo and willing to give us some feedback in advance of the public release, please get in touch (here, or avi@stripe.com).

      10:54 AM - 19 May 2018
      • 1 Retweet
      • 11 Likes
      • Jorge ∬ ⌬ + ☢ Andrew Walkingshaw Thomas Lockney (he/him) Jeff Sarnat Adam Pingel Vaibhav Mallya 𝕄𝕚𝕠 Ben Matasar
      8 replies 1 retweet 11 likes
        1. New conversation
        2. Ryan Richt‏ @ryan_richt May 20
          Replying to @avibryant

          @avibryant does that mean you have AutoDiff on arbitrary Scala working!!? We’d still likely use both your thing and ScalaStan. We’d love to private beta (and hope you’ll consider EvilPlot for your Bayesian posterior and diagnostic reports!)

          1 reply 1 retweet 1 like
        3. Avi Bryant‏ @avibryant May 20
          Replying to @ryan_richt

          1/ EvilPlot looks completely awesome and I am eager to get it integrated; and please email me to get into the beta, I would hugely appreciate your feedback.

          1 reply 0 retweets 0 likes
        4. Avi Bryant‏ @avibryant May 20
          Replying to @avibryant @ryan_richt

          2/ it's autodiff on arbitrary Scala that operates on a numeric type which represents an unknown double and does not allow you to directly inspect its value (so you can't, say, use it to index into an array - just do math).

          1 reply 1 retweet 1 like
        5. Avi Bryant‏ @avibryant May 20
          Replying to @avibryant @ryan_richt

          3/ whatever your Scala code is that manipulates these, ultimately the function it produces (and its gradient) gets compiled down to allocation-free generated JVM bytecode for Array[Double] => Array[Double]

          0 replies 1 retweet 2 likes
        6. End of conversation
        1. New conversation
        2. ∬ ⌬ +  ☢‏ @zaxtax May 22
          Replying to @avibryant

          How easy is it to add new inference algorithms? How easy is it to compose existing inference algorithms?

          1 reply 0 retweets 0 likes
        3. Avi Bryant‏ @avibryant May 22
          Replying to @zaxtax

          We've really given no thought to composing inference algorithms so I wouldn't expect that to be easy. In terms of adding new inference algorithms, I guess it would depend a lot; eg particle filtering, I think would be pretty hard to add; more variants of MCMC would be easy.

          1 reply 0 retweets 0 likes
        4. Avi Bryant‏ @avibryant May 22
          Replying to @avibryant @zaxtax

          Ironically the starting point was a Scala implementation of https://dl.acm.org/citation.cfm?id=2804317 … which has a focus on composition and also particle filtering, but we've diverged greatly from that now.

          0 replies 0 retweets 0 likes
        5. End of conversation
        1. New conversation
        2. Jorge M‏ @hibikir1 May 20
          Replying to @avibryant

          I so want to see how much better/worse this works than Scalastan

          1 reply 0 retweets 0 likes
        3. Avi Bryant‏ @avibryant May 20
          Replying to @hibikir1

          Have you used Scalastan for anything?

          1 reply 0 retweets 0 likes
        4. Jorge M‏ @hibikir1 May 20
          Replying to @avibryant

          It is developed at my current employer (which also released EvilPlot). We use it for real things, but a science startup is very different from Stripe

          1 reply 0 retweets 1 like
        5. Avi Bryant‏ @avibryant May 20
          Replying to @hibikir1

          Oh cool. I’d be very interested to get feedback from you and/or your colleagues (even if it’s just examples showing why scalastan is better :) Send me an email if you want early access.

          0 replies 0 retweets 0 likes
        6. End of conversation
        1. New conversation
        2. Cam DP‏ @Cmrn_DP May 19
          Replying to @avibryant

          What are y’all using it for?

          1 reply 0 retweets 0 likes
        3. Avi Bryant‏ @avibryant May 19
          Replying to @Cmrn_DP

          Time series forecasting.

          1 reply 0 retweets 0 likes
        4. Avi Bryant‏ @avibryant May 19
          Replying to @avibryant @Cmrn_DP

          BTW would be very curious to hear your feedback (either now or once it's released) - your book was a very useful resource while we were working on it.

          1 reply 0 retweets 1 like
        5. Cam DP‏ @Cmrn_DP May 19
          Replying to @avibryant

          thanks for the kind words =) I'm working on a side-bayesian project now. So I'd be interested in seeing it now, but probably won't have much time for a few weeks to give feedback.

          0 replies 0 retweets 0 likes
        6. End of conversation
        1. New conversation
        2. Sebastian Bensusan‏ @sebasbensu May 19
          Replying to @avibryant

          Is it reasonable to use it from another JVM language, not Scala?

          1 reply 0 retweets 0 likes
        3. Avi Bryant‏ @avibryant May 19
          Replying to @sebasbensu

          Interesting question. It hasn't been designed with that in mind, and the high level modeling API is very Scala-specific, but I suspect someone could build a shim for the lower levels.

          0 replies 0 retweets 1 like
        4. End of conversation
        1. Ben Matasar‏ @matasar May 19
          Replying to @avibryant

          me me me

          0 replies 0 retweets 1 like
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        1. negative diff author‏ @Craig_McNamara May 24
          Replying to @avibryant

          I’m interested.

          0 replies 0 retweets 0 likes
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        1. Vaibhav Mallya‏ @mallyvai May 19
          Replying to @avibryant

          ^ @mattcastillon

          0 replies 0 retweets 0 likes
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