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o_guest's profile
Olivia Guest | Ολίβια Γκεστ
Olivia Guest | Ολίβια Γκεστ
Olivia Guest | Ολίβια Γκεστ
@o_guest

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Olivia Guest | Ολίβια Γκεστ

@o_guest

• goth gremlin • computational cognitive/neuroscience modeling • geek & techish Cypriot • plant aficionada • came up with #bropenscience • http://neuroplausible.com  •

Τότεναμ, Λονδίνο & Cyprus
olivia.science
Joined October 2015

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    1. Joseph Austerweil‏ @JoeAusterweil Feb 25
      • Report Tweet
      Replying to @marcolin91 @ProfData and

      Integral vs separable dimensions with the Bayesian generalization model

      1 reply 0 retweets 2 likes
    2. Esther Mondragón‏ @twitemp1 Feb 25
      • Report Tweet
      Replying to @JoeAusterweil @marcolin91 and

      Although I think that representations can be defined at a computational level, we often work with algorithmic-level definitions as @ProfData has explained. In other words, representations are part of the model and need to be specified algorithmically.

      1 reply 0 retweets 2 likes
    3. Joseph Austerweil‏ @JoeAusterweil Feb 25
      • Report Tweet
      Replying to @twitemp1 @marcolin91 and

      Ah I may have misunderstood Brad. That seems reasonable as what counts at the algorithmic level as a representation

      1 reply 0 retweets 2 likes
    4. Marco lin‏ @marcolin91 Feb 25
      • Report Tweet
      Replying to @JoeAusterweil @twitemp1 and

      If I understand the integral vs separable from your 2010 paper, I do believe it is very interesting though, and imo can be seen as an embedded algorithmic-computational relation that effectively 'closes' the representational process, if one views systems as embedding sub-systems

      1 reply 0 retweets 2 likes
    5. Marco lin‏ @marcolin91 Feb 25
      • Report Tweet
      Replying to @marcolin91 @JoeAusterweil and

      Particularly interesting (imo), is that the discussion often is about grounding (Reps) towards implementation within a system, but what about grounding the other way around towards computational? To adaptively situate/couple, one must establish the comp problem/hypothesis space

      1 reply 0 retweets 3 likes
    6. Marco lin‏ @marcolin91 Feb 25
      • Report Tweet
      Replying to @marcolin91 @JoeAusterweil and

      To extend the speculaiton a bit more explicitly: It suggests embedded 'Marrian hierarchies' that point to a key qualifier for an agent possessing representations {R}: to possess a systematicity, a good regulator if you will, of the set of {R} and the processes of utilising them

      2 replies 0 retweets 2 likes
    7. Bradley Love‏ @ProfData Feb 25
      • Report Tweet
      Replying to @marcolin91 @JoeAusterweil and

      No one's going to like this, but I don't think it makes sense to talk of representations at the computational level because there is no processing there. It's the level of problem description. Matt Jones and I talk about that in our BBS paper from several years ago.

      3 replies 1 retweet 6 likes
    8. Marco lin‏ @marcolin91 Feb 25
      • Report Tweet
      Replying to @ProfData @JoeAusterweil and

      I'll check the awesome sounding bayesian enlightenment! But I was just trying to build bridges in conversation. How to optimally leverage the AlgoBridges, needs imo exploring the boundaries & diversity of algorithmic space, and how relations to the other levels change therein

      1 reply 0 retweets 2 likes
    9. Olivia Guest | Ολίβια Γκεστ‏ @o_guest Feb 25
      • Report Tweet
      Replying to @marcolin91 @ProfData and

      It's this! ☺️ Jones, M. & Love, B. C. (2011). Bayesian Fundamentalism or Enlightenment? On the Explanatory Status and Theoretical Contributions of Bayesian Models of Cognition. Behavioral and Brain Sciences.https://doi.org/10.1017/S0140525X10003134 … PDF: http://bradlove.org/papers/JonesLove2011all.pdf …

      1 reply 2 retweets 6 likes
    10. Marco lin‏ @marcolin91 Feb 25
      • Report Tweet
      Replying to @o_guest @ProfData and

      Thank you will read this today!

      1 reply 0 retweets 2 likes
      Olivia Guest | Ολίβια Γκεστ‏ @o_guest Feb 25
      • Report Tweet
      Replying to @marcolin91 @ProfData and

      IMHO the field actually self-corrected as a reaction to this and other papers calling out the fundamentalists. A nice thought that slowly but surely we find better ways to do, at least cognitive, science.

      3:29 AM - 25 Feb 2019
      • 3 Likes
      • Esther Mondragón KordingLab Marco lin
      2 replies 0 retweets 3 likes
        1. KordingLab‏ @KordingLab Feb 25
          • Report Tweet
          Replying to @o_guest @marcolin91 and

          Being part of that field, I think we have over the last decade or so tried to considerably improve. Statistics of the world to define priors. Separate likelihood tests. Acknowledging that behavior is not optimal. Generalization tests. Comparison across different Bayesian models.

          0 replies 0 retweets 4 likes
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        2. Olivia Guest | Ολίβια Γκεστ‏ @o_guest Feb 25
          • Report Tweet
          Replying to @o_guest @marcolin91 and

          [From what I know other subfields have deeper issues than this that involve more seriousness violations of the scientific method and misconduct. 😂 Sorry, couldn't resist. I'm a terrible human.]

          1 reply 0 retweets 2 likes
        3. Bradley Love‏ @ProfData Feb 25
          • Report Tweet
          Replying to @o_guest @marcolin91 and

          Yeah, different types of models make different types of claims and should be evaluated on different types of data, so it’s important to be clear.

          0 replies 0 retweets 4 likes
        4. End of conversation

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