SueYeon Chung

@s_y_chung

computational neuroscientist , visiting fellow in computation . interested in manifolds and sequential structures in the brain and deep nets

Vrijeme pridruživanja: studeni 2011.

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  1. proslijedio/la je Tweet
    22. sij

    My blogpost on how & why we use convolutional neural networks as a model of the visual system is probably the most read thing I've ever written and it's now been expanded & updated into a proper review article, complete with 136 references & 5 new figures!

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  2. proslijedio/la je Tweet
    20. pro 2019.

    Excited to post my preprint about RNNs, dynamics, and ! Here’s a quick explaining the main ideas: 1/10

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  3. proslijedio/la je Tweet
    20. pro 2019.

    Interested in how neuroscience can inspire better AI? Come to NAISys, March 24-28 Abstracts (1 page) due Jan 10 registration {Please RETWEET ME}

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  4. 12. pro 2019.

    Thanks for coming to see our poster on untanglement of neural manifolds in speech systems ! Had a blast collaborating with and McDermott Lab at MIT !

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  5. proslijedio/la je Tweet

    I am looking forward to ! Let's remind ourselves to use scientific and empirical evidence to back our claims, and to be kind to each other and set a good example to current and future generations : )

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  6. proslijedio/la je Tweet
    20. stu 2019.

    The last piece of work from my postdoc, which I am most proud of: how to split a populaton of neurons into ON and OFF. Elegant math and many experimental predictions : Functional diversity among sensory neurons from efficient coding principles

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  7. proslijedio/la je Tweet

    New pub by grad students Salomon Muller and Abigail Zadina and Drs. Abbott and Sawtell. Check it out!

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  8. proslijedio/la je Tweet

    I think an important part of life satisfaction is to find the things that really motivate you, and pursue then uncompromisingly. You won't do great work by constantly forcing yourself to do things that don't genuinely excite you.

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  9. proslijedio/la je Tweet
    29. lis 2019.

    Lovely explanations of the slicing problem by Jessica Lee. Basis of theories of machine learning from the 60s but originally due to 19th century Swiss mathematician Schlafli

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  10. proslijedio/la je Tweet
    28. lis 2019.

    Novelty == value! Now out: our review of RL/ML algorithms that integrate value across novelty and external rewards to drive learning. Our take: this work informs why novelty representations manifest as they do in IT. Kudos to & Vahid Mehrpour!

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  11. 27. lis 2019.

    Neuro-ML Twitter: What's your favorite software/website to work on a poster with multiple collaborators simultaneously and remotely (ie Overleaf or a google doc, but for a poster)?

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  12. proslijedio/la je Tweet
    23. lis 2019.

    POSTDOCTORAL POSITION in my lab (Jazlab) at MIT to investigate the computational principles and neural mechanisms of inferential reasoning using cognitive maps in the hippocampus, entorhinal cortex, and other candidate brain areas. See more info at

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  13. proslijedio/la je Tweet
    7. lis 2019.

    Our most recent work on “computation-through-dynamics.” We propose that cognitive control can be understood in terms of principles of motor control: 1) control, 2) simulation, and 3) estimation. Many thanks to , CJ Chang, Evan Remington

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  14. proslijedio/la je Tweet
    1. lis 2019.

    ICML 2021 in SEOUL, KOREA!

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  15. proslijedio/la je Tweet
    24. ruj 2019.

    (neuro)scientists are increasingly waking up to the realities of the climate crisis, and are starting to take action as individuals and scientific communities. feel overwhelmed? not sure where to start? i've started a 'beginners guide' with resources:

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  16. proslijedio/la je Tweet
    19. ruj 2019.

    giving a nice talk on geometry & separability of perceptual manifolds (w ) including CNN & NHP data (from lab), and wrapping up with how the brain may do few shot learning, despite technical difficulties (look at the mike!)

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  17. proslijedio/la je Tweet
    6. ruj 2019.

    Looking forward to our BCCN half-day workshop on "Neural computation through recurrent dynamics: from theory to experiment and back" with Francesca Mastrogiuseppe. Berlin, Sep 17, 14:00

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  18. proslijedio/la je Tweet
    30. kol 2019.

    New in : Some images are easier to remember than others. Why? In addition to the 'spike pattern' coding scheme assoc. w/ identity, IT cortex also codes info. by spike numbers, and pop. response magnitude is a strong predictor of memorability.

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  19. 26. srp 2019.

    More RA positions available on the topic of structure and sequences in RNNs in the fall semester (and beyond)! Contact me if you are looking for a BA/MA thesis topic for the next year, or know someone who does!

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  20. proslijedio/la je Tweet
    10. lip 2019.

    New paper by , Nancy Kanwisher, me, and Bevil Conway: The key finding: fMRI maps of frequency selectivity are comparably robust in humans and macaques, but response preferences for harmonic tones over noise are much stronger in humans.

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