Sea Mammal

@walrus_md

Vrijeme pridruživanja: siječanj 2015.
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  1. proslijedio/la je Tweet
    25. ruj 2019.

    Our new preprint on the ‘Neural dynamics of perceptual inference and its reversal during imagery’ with and is out now! We reveal feedforward and feedback dynamics of stimulus processing during perception and imagery. A thread 1/N

    6 replies 50 proslijeđenih tweetova 126 korisnika označava da im se sviđa
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  2. proslijedio/la je Tweet
    31. ožu 2019.

    Just finished this by - to write so well and so clearly about statistics is a rare skill. Reminds me of Doug Altman’s papers. All doctors should read it, whether they are researchers or not.

    10 replies 61 proslijeđeni tweet 255 korisnika označava da im se sviđa
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  3. proslijedio/la je Tweet
    15. ožu 2019.

    This. Don't waste time on domain specific tricks. Do work on abstract & general inductive biases like smoothness, relational structure, compositionality, in/equivariance, locality, stationarity, hierarchy, causality. Do think carefully & deeply about what is lacking in AI today.

    The contrast btw Rich Sutton and Shimon Whiteson re the value of injecting human knowledge into models is a good definition of the word “principled”. Sutton‘s Bitter Lesson is that ad hoc tricks don’t hold up. ‘s Sweet Lesson us that deeper (more principled) ideas do.
    8 replies 96 proslijeđenih tweetova 399 korisnika označava da im se sviđa
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  4. proslijedio/la je Tweet
    4. sij 2019.

    So every time we jump to the conclusion that evolution favors a specific human behavior without a BOATLOAD of truly cross-cultural proof, we're being patently ridiculous. We're supposed to prefer different things, behave differently, think differently. It's a feature, not a bug.

    63 proslijeđena tweeta 433 korisnika označavaju da im se sviđa
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  5. proslijedio/la je Tweet
    3. sij 2019.

    Question for neuro people: can you say concretely what you feel this style of analysis provides? I too think it has been important for my thinking, but I can't exactly say why that is or what really crucial advance it has offered

    The idea of neural activity as a trajectory through a low-d state space has become really important to my understanding of the brain, but as far as I can tell there aren't many efforts to explain it to a broader audience
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    14 replies 14 proslijeđenih tweetova 55 korisnika označava da im se sviđa
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  6. proslijedio/la je Tweet
    31. srp 2018.

    Learn: 1. linear algebra well (e.g. matrix math) 2. calculus to an ok level (not advanced stuff) 3. prob. theory and stats to a good level 4. theoretical computer science basics 5. to code well in Python and ok in C++ Then read and implement ML papers and *play* with stuff! :-)

    Hey Shane I’m currently 17 from London England and am very passionate about AI, also learning about in-depth human needs. What would be the 5 pieces of advice and tips you would give to a young person like me?
    432 proslijeđena tweeta 1.505 korisnika označava da im se sviđa
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  7. proslijedio/la je Tweet
    5. tra 2018.

    If you had to teach some motivated, intelligent people to program (for the first time) in Python, what books / online resource would you use?! Any standouts?

    16 replies 11 proslijeđenih tweetova 21 korisnik označava da mu se sviđa
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  8. proslijedio/la je Tweet
    19. ožu 2018.

    Reasoning challenges for machine learning by Allen Institute. So so fascinating.

    1 reply 15 proslijeđenih tweetova 53 korisnika označavaju da im se sviđa
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  9. proslijedio/la je Tweet
    17. ožu 2018.

    "How to solve 90% of NLP problems: a step-by-step guide" by @EmmanuelAmeisen

    13 proslijeđenih tweetova 41 korisnik označava da mu se sviđa
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  10. proslijedio/la je Tweet
    15. ožu 2018.

    A beautiful, visual statistics textbook: "Seeing Theory – A visual introduction to probability and statistics.” I shared this a year ago, when it was already very cool. But the page now got a major upgrade by the authors and is now just incredibly cool!

    733 proslijeđena tweeta 1.667 korisnika označava da im se sviđa
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  11. proslijedio/la je Tweet
    11. ožu 2018.

    Highly recommend this paper for practitioners of / those with an interest in Evolutionary Computation and Artificial Life. Overview of the many ways that evolution will "cheat" and hack its way around your oh-so-clever reward function!

    10 replies 200 proslijeđenih tweetova 552 korisnika označavaju da im se sviđa
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  12. proslijedio/la je Tweet
    7. ožu 2018.

    The Lighthill debate (1973): Extraordinary video to understand the history of and how winter came. Many arguments on both sides are still valid today about approaches

    59 proslijeđenih tweetova 100 korisnika označava da im se sviđa
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  13. proslijedio/la je Tweet
    6. ožu 2018.

    Syntax-Directed Variational Autoencoder for Structured Data, a VAE for structured discrete objects where the grammar is known. blog post: paper: open review:

    107 proslijeđenih tweetova 291 korisnik označava da mu se sviđa
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  14. proslijedio/la je Tweet
    4. ožu 2018.

    New blog post: Requests for research. A collection of interesting research directions around transfer learning and NLP

    13 replies 238 proslijeđenih tweetova 676 korisnika označava da im se sviđa
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  15. proslijedio/la je Tweet
    28. velj 2018.

    "Evolutionary Robotics Course" by Video Lectures 🎬

    14 proslijeđenih tweetova 21 korisnik označava da mu se sviđa
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  16. proslijedio/la je Tweet
    25. sij 2018.

    AI2 Research Engineer shows you how to run models on free GPUs using Google’s Colab notebooks! Learn more:

    15 proslijeđenih tweetova 26 korisnika označava da im se sviđa
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  17. proslijedio/la je Tweet
    12. velj 2018.

    Great talk by Andy Clark on predictive processing as a model for integrating the many core information processing strategies we use in perception. also here's a podcast on the topic

    1 reply 9 proslijeđenih tweetova 16 korisnika označava da im se sviđa
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  18. proslijedio/la je Tweet
    14. pro 2017.

    Deep Learning, Language and Cognition: Video of an introductory talk on computational linguistics for a broad audience—from hand-written rules to modern neural net models—by Christopher Manning () at IAS, Princeton.

    226 proslijeđenih tweetova 517 korisnika označava da im se sviđa
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  19. proslijedio/la je Tweet
    29. sij 2018.

    The difference between weak and strong non-ergodicities, based on Peters and Gell-Mann (2016) cc:

    6 replies 56 proslijeđenih tweetova 185 korisnika označava da im se sviđa
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  20. proslijedio/la je Tweet
    29. sij 2018.

    Great news - the second version of the amazing deep learning tutorial has been launched! I did the first version and I learned a ton, highly recommended

    5 proslijeđenih tweetova 14 korisnika označava da im se sviđa
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