Gabe Erion

@gabeerion

MD/PhD student at University of Washington working on machine learning in healthcare. Interested in ML interpretability, cost-effectiveness, and causality.

Vrijeme pridruživanja: ožujak 2011.

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  1. proslijedio/la je Tweet
    29. stu 2018.

    As requested, slower graphs! Also added a graph on collider bias, the webpage explanation helps there. These graphs are intended to show what standard causal inference methods actually *do* to data, and how they work. This is what controlling for a binary variable looks like:

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  2. proslijedio/la je Tweet
    15. sij

    Excited to have our article about feature attribution baselines out in , with and .

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  3. proslijedio/la je Tweet
    15. sij

    Yesterday afternoon legislators in South Dakota filed HB 1057, a bill that would put doctors in prison for providing medically necessary care for transgender youth. If that wasn’t shocking enough, now they’ve scheduled the bill to be heard THIS FRIDAY at 7:45 AM.

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  5. proslijedio/la je Tweet
    Odgovor korisnicima i sljedećem broju korisnika:

    Note, the Union Station Great Hall (adjacent to the International District/Chinatown Link light rail station) is open to the public from 6 a.m. - 8 p.m. this week for those who need to get out of the cold.

    Union Station in downtown Seattle on a wintry day.
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  6. 14. sij

    I'm very grateful to have contributed a little to this awesome work by Joe!

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  7. 29. pro 2019.

    "It's art, it's not just about teeth!" -

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  8. proslijedio/la je Tweet
    21. pro 2019.

    This is great esp the number of female attendees going from 2% last year to 20% this year. However, all this diversity & inclusion that is experiencing comes at a high price for those who do the actual work.

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  9. proslijedio/la je Tweet
    21. pro 2019.

    game night with the fam

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  10. proslijedio/la je Tweet

    RT if you're a scientist who acknowledges that neither gender nor sex is binary, and would very much like TERFs to stop referring to science when attempting to justify their bigotry. 💖

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  11. proslijedio/la je Tweet

    Oh yeah if you want Good magic for kids give them 's stuff instead

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  12. proslijedio/la je Tweet
    14. pro 2019.

    The state of DeepFakes in 2019 from at ... Stop worrying about fake news applications and focus on the real issue: 96% of DeepFake content is used for pornographic, nonconsensual digital assaults on women.

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  13. proslijedio/la je Tweet
    14. pro 2019.

    And Nicasia presenting her work on multi-task deep learning for Alzheimer’s Disease !

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  14. proslijedio/la je Tweet
    14. pro 2019.

    Also really glad to be able to stream talks from other students in the lab, including Ayse presenting her work on DeepProfile, an ensemble VAE based method for cancer transcriptome analysis (also with ) !

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  15. proslijedio/la je Tweet
    14. pro 2019.

    Really sad to have not been able to make it to Vancouver today for , but so proud of undergrad student Will Chen for presenting our project on interpretable TF binding prediction !! He’s only a sophomore student, so impressive! (cc: )

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  16. proslijedio/la je Tweet
    11. pro 2019.

    Super excited to have my first first-author paper out in the world. And even more excited it’s a Python package when I barely knew how to code at the start of grad school! Also, I have a small sample size for comparison, but the JOSS submission/review process was excellent!

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  17. proslijedio/la je Tweet

    No matter your candidate, you have to recognize that going from the most diverse field ever in January to a potentially all-white debate stage in December is catastrophic. The implicit racism and sexism of "electability" is deeply damaging to democracy.

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  18. proslijedio/la je Tweet

    "In all, Little Misfortune is a polished and compelling story that leads you down a humorous and morbid path." Our reviewed the Little Misfortune by :

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  19. proslijedio/la je Tweet
    29. stu 2019.

    we’re doing a family dnd campaign and i have to say i am so proud of our new dm

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

    Explaining Models by Propagating Shapley Values of Local Components. (arXiv:1911.11888v1 [cs.LG])

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