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patrickmineault's profile
Patrick Mineault
Patrick Mineault
Patrick Mineault
@patrickmineault

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Patrick Mineault

@patrickmineault

Computational neuroscience, vision research, Python, data science, open science, ML, brains. Previously engineer @ Google, Facebook. Updates from http://xcorr.net 

Montreal, QC, CA
xcorr.net
Joined April 2011

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    Patrick Mineault‏ @patrickmineault 9 Apr 2020

    OpenAI goes Hubel & Wiesel, Chapter 2 https://distill.pub/2020/circuits/early-vision/ … (1/)

    12:05 PM - 9 Apr 2020
    • 35 Retweets
    • 131 Likes
    • daksh.eth ⟠ Hiring Engineers Rish Mitchell Gordon Rajiv Chauhan Guillermo González de Garibay Daniel Borek Gopala KR Frederik Laboyrie kalvyn
    3 replies 35 retweets 131 likes
      1. New conversation
      2. Patrick Mineault‏ @patrickmineault 9 Apr 2020

        The authors describe the preferred stimuli of the lower layers of InceptionV1. Simple cells & color contrast cells pool into complex cells.pic.twitter.com/xazqnHZCfg

        1 reply 0 retweets 3 likes
        Show this thread
      3. Patrick Mineault‏ @patrickmineault 9 Apr 2020

        Starting in layer conv2d2 we start seeing more complicated features that look fairly V2 like - line and curve detectors, as well as various texture unitspic.twitter.com/1Vw0uRZmWh

        1 reply 0 retweets 3 likes
        Show this thread
      4. Patrick Mineault‏ @patrickmineault 9 Apr 2020

        Lots of specialized detectors for circles starting in layer 3 and above. It starts to look very V4 like.pic.twitter.com/02XevCXwfb

        1 reply 0 retweets 4 likes
        Show this thread
      5. Patrick Mineault‏ @patrickmineault 9 Apr 2020

        Starting in mixed3b, the network sure starts to like eyeballs and other complex featurespic.twitter.com/VOcbwqXVP3

        1 reply 0 retweets 4 likes
        Show this thread
      6. Patrick Mineault‏ @patrickmineault 9 Apr 2020

        There's a lot of interesting parallels between different layers of the model and what we know about the early (and not-so-early) visual cortex. It would be nice to see fine-grained measurements of alignments between ANNs and BNNs sorted by feature type (i.e. micro-BrainScores)

        1 reply 0 retweets 5 likes
        Show this thread
      7. Patrick Mineault‏ @patrickmineault 9 Apr 2020

        At the same time, there's a lot of representation of features that haven't been well-studied: second-order edges defined by spatial frequency, joint color and shape tuning, eyes, pattern selectivity in V4, etc.

        2 replies 0 retweets 3 likes
        Show this thread
      8. Patrick Mineault‏ @patrickmineault 9 Apr 2020

        I would love to see if there's an eye space in visual cortex in the same way that there's face spacepic.twitter.com/3rIhv9OL7O

        1 reply 0 retweets 6 likes
        Show this thread
      9. Patrick Mineault‏ @patrickmineault 9 Apr 2020

        The preferred stimulus representation used by the authors doesn't show nonlinear feature integration or invariant subspaces: how can we do that with this type of visualization?

        2 replies 0 retweets 4 likes
        Show this thread
      10. Patrick Mineault‏ @patrickmineault 9 Apr 2020

        I would love to see a video showing highlighting the invariant subspaces of a given neuron. And I think nonlinear feature integration (and/like) could be highlighted using model reductions (fitting a model to a model), perhaps with canonical nonlinearitieshttps://www.ncbi.nlm.nih.gov/pubmed/18254695 

        1 reply 0 retweets 3 likes
        Show this thread
      11. Patrick Mineault‏ @patrickmineault 9 Apr 2020

        I was skeptical, but I think this approach is turning out pretty fruitful! Excited for the next batch of articles to come out.

        2 replies 0 retweets 3 likes
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      12. End of conversation

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