Gatsby Computational Neuroscience Unit

@GatsbyUCL

Research in computational and theoretical neuroscience, and statistical machine learning. Funded by the Gatsby Charitable Foundation. Based in

London, United Kingdom
Vrijeme pridruživanja: rujan 2019.

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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. This week we welcome from to talk about "Deep learning on graphs and manifolds: going beyond Euclidean data". This Wed 22nd @ 4pm, Ground Floor LT, 25 Howland Street. All welcome.

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  3. proslijedio/la je Tweet
    1. sij

    Machine Learning Summer School 28 June - 10 July 2020 at the Max Planck Institute for Intelligent Systems, Tübingen, Germany. Application deadline: 11 Feb 2020. All welcome to apply!

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  4. We are looking forward to speaking at Gatsby next week! He will give two talks on Wed 15th of Jan, one about his career & struggles in science () and another about human planning in large state spaces (). All welcome! SWC Ground floor LT, 25 Howland Street.

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  5. proslijedio/la je Tweet
    8. sij

    Also, I will be giving talks at and (Neurotheory). I will speak both about the series itself (and how to start your own) and about my own life/career story, with an emphasis on struggles, doubts, detours, and failures.

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  6. proslijedio/la je Tweet
    8. sij

    Next week, I will be speaking at , , and (Neurotheory) on human planning in large state spaces. I look forward to talking to many of you there, esp. students and postdocs. Details below. Background reading:

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  7. Our 2020 external seminar series kicks off with Chand Chandrasekaran from Boston University who will speak about Single Trial Neural Circuit Dynamics Underlying Perceptual Decision-Making. This Wed 8th Jan @ 4pm, SWC ground floor LT, 25 Howland Street.

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

    We learned a lot in 2019. One of our key goals was to increase interdisciplinary work with . Read more here:

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  9. proslijedio/la je Tweet

    The UCL Excellence Fellowship is open for applications. The programme supports candidates with exceptional track record to establish independence. Candidates from life, medical, clinical, applied and population health science are welcome to apply

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

    You can now test dependence of survival times on covariates in the presence of right censoring (which can also depend on the covariates!) Something for that long flight back from :) With Tamara Fernandez, David Rindt and

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    10. pro 2019.

    Wasserstein gradient flow of the MMD, in Tuesday's afternoon poster session at Relates to the dynamics of neural net training and to understanding GAN convergence. With

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

    Excited to be giving a tutorial with and tomorrow, on "Interpretable Comparison of Distributions and Models" at 11:15 AM -- 01:15 PM @ West Exhibition Hall A.

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

    Glad to present our poster at ! TLDR: an online smoothing algorithm for generic state-space models, a computation the brain performs all the time. Poster: Thu 12th 10:45 -12:45 @ East Hall B + C #180 Paper:

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

    Very excited to present our work on successor representations and state uncertainty as an oral next week at , Vancouver!

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  17. Just over 2 weeks left for early applications to be submitted to our Joint Gatsby-SWC Group Leader position at the interface of and ! Apply here by 30th of November:

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  19. We have a unique Group Leader opportunity to work at the interface of Machine Learning and Neuroscience! We’re looking for an exciting and interdisciplinary researcher keen to contribute to an algorithmic understanding of the brain. More details:

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  20. proslijedio/la je Tweet
    24. lis 2019.

    Natural gradient: it's not just for Fisher-Rao! Wasserstein 2 natural gradient using a kernel estimate: , Wuchen Li,

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