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  1. proslijedio/la je Tweet
    27. sij

    New NLP News: NLP Progress, Restrospectives and look ahead, New NLP courses, Independent research initiatives, Interviews, Lots of resources (via )

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  2. 21. ožu 2018.

    Understanding Deep Learning through Neuron Deletion

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  3. proslijedio/la je Tweet

    Check out AmoebaNets, state-of-the-art programmatically evolved from the Google Brain team (), and one of the latest results from our broader efforts →

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  4. proslijedio/la je Tweet
    6. ožu 2018.

    How do do what they do? Today, published a new article exploring how networks make decisions. Also released is Lucid, a neural network visualization library, along with colab notebooks to produce your own visualizations →

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  5. proslijedio/la je Tweet
    2. ožu 2018.
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  6. proslijedio/la je Tweet
    2. velj 2018.
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  7. proslijedio/la je Tweet
    29. sij 2018.

    Our new paper in the Journal of Artificial Intelligence Research (JAIR) demonstrates how deep neural networks can be extended to generalise visually and symbolically.

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  8. proslijedio/la je Tweet
    17. sij 2018.

    Our latest paper in describes a surprisingly simple way to understand asymmetric games, with possible implications for economics, empirical game theory and environments where multiple AI systems operate

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  9. proslijedio/la je Tweet
    15. sij 2018.

    Releasing gradient checkpointing - a package for fitting bigger Tensorflow models onto your GPU. By trading off memory usage against a 20% increase in computation time, we’ve used this to train 10X larger models:

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  10. proslijedio/la je Tweet
    5. sij 2018.

    Recent Advances in Recurrent Neural Networks (fundamentals, recent advances & research challenges)

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  11. proslijedio/la je Tweet
    21. pro 2017.

    Today, we are publishing some Google Assistant evaluation guidelines for those who are researching improvements in voice interactions with technology. It is our hope that they will help the community build and evaluate their own systems. Learn more at →

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  12. proslijedio/la je Tweet
    18. pro 2017.

    Learn about Neural Image Assessment (NIMA), a deep CNN that is trained to rate the technical and aesthetic qualities of an image, scoring them reliably and with high correlation to human perception. Oh, and it can be used to enhance images too! →

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  13. proslijedio/la je Tweet
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  14. proslijedio/la je Tweet
    11. pro 2017.

    This one is a very good introduction to the most common building blocks of recent Deep Learning architectures.

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  15. proslijedio/la je Tweet
    5. pro 2017.

    The generalization of AlphaGo Zero, called AlphaZero, achieves superhuman performance in all of Chess, Shogi, and Go. Starting from random play, and given no domain knowledge. New paper from DeepMind:

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  16. proslijedio/la je Tweet
    28. stu 2017.

    In order to build better and more robust DNN-based systems, one must be able to effectively interpret the models. We introduce a simple and scalable method to both compare and interpret the representations learned by DNNs

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  17. proslijedio/la je Tweet
    27. stu 2017.

    Introducing Population Based Training: a new method for automatically performing online hyperparameter adaptation and model selection by exploiting populations of neural networks

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  18. proslijedio/la je Tweet

    use gradient magnitude as a signal for gradient importance. Sort your gradients, find a threshold, clip your gradients, exchange sparse gradients, win.

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  19. proslijedio/la je Tweet
    15. stu 2017.

    Today we are announcing SLING, an experimental system for parsing natural language text directly into a representation of its meaning as a semantic frame graph. We hope the research community finds SLING useful! Check it out at

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  20. proslijedio/la je Tweet
    7. stu 2017.

    Have you ever wondered what goes on inside ? Learn how explores feature visualization at

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