Applications of Deep Neural Networks [pdf]

This page summarizes the projects mentioned and recommended in the original post on news.ycombinator.com

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  • compare_gan

    Discontinued Compare GAN code.

    Sure thing! https://github.com/google/compare_gan/issues/54

    It’s not much of a writeup. It’s basically saying, hey, this is zero when it should be one.

    The results were dramatic. It went from blobs to replicating the biggan paper almost perfectly. I think we’re at a FID of 11 or so on imagenet.

    Stole a year of my life to track it down. But it was a puzzle I couldn’t put down. It haunted my dreams. I was tossing and turning like, but why won’t it work... why won’t it work...

  • deep-diamond

    A fast Clojure Tensor & Deep Learning library

    If I may drop in with a bit of shameless self-promotion.

    My "Deep Learning for Programmers: A Tutorial with CUDA, OpenCL, DNNL, Java, and Clojure" book explains and executes every single line of code interactively, from low level operations to high-level networks that do everything automatically. The code is built on the state of the art performance operations of oneDNN (Intel, CPU) and cuDNN (CUDA, GPU). Very concise readable and understandable by humans.

    https://aiprobook.com/deep-learning-for-programmers/

    Here's the open source library built throughout the book:

    https://github.com/uncomplicate/deep-diamond

    Some chapters from the beginning of the book are available on my blog, as a tutorial series:

    https://dragan.rocks

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  • mmaction2

    OpenMMLab's Next Generation Video Understanding Toolbox and Benchmark

    shameless ad: try mmaction2, where every result is reproducible https://github.com/open-mmlab/mmaction2 . Modelzoo: https://mmaction2.readthedocs.io/en/latest/modelzoo.html

NOTE: The number of mentions on this list indicates mentions on common posts plus user suggested alternatives. Hence, a higher number means a more popular project.

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