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    TF-Slim: A Lightweight Library for Defining, Training and Evaluating Complex Models in TensorFlow 

    Silberman, Nathan (Georgia Institute of Technology, 2017-09-07)
    TF-Slim is a TensorFlow-based library with various components. These include modules for easily defining neural network models with few lines of code, routines for training and evaluating such models in a highly distributed ...
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    Deep Networks for Pixel Level Inference with Applications to Medical Imaging 

    Chopra, Sumit (Georgia Institute of Technology, 2017-09-26)
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    An overview of deep learning frameworks and an introduction to PyTorch 

    Chintala, Soumith (2017-09-06)
    In this talk, you will get an exposure to the various types of deep learning frameworks – declarative and imperative frameworks such as TensorFlow and PyTorch. After a broad overview of frameworks, you will be introduced ...
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    The New Machine Leaming Center at GA Tech: Plans end Aspirations 

    Essa, Irfan (Georgia Institute of Technology, 2017-03-01)
    The Interdisciplinary Research Center (IRC) for Machine Learning at Georgia Tech (ML@GT) was established in Summer 2016 to foster research and academic activities in and around the discipline of Machine Learning. This ...
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    Sum-Product Networks: The Next Generation of Deep Models 

    Domingos, Pedro (2017-04-19)
    The two main types of deep learning are function approximation and probability estimation. Function approximators like convolutional neural networks are robust and allow for real-time inference, but are very inflexible, ...

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    AuthorChintala, Soumith (1)Chopra, Sumit (1)Domingos, Pedro (1)Essa, Irfan (1)Silberman, Nathan (1)SubjectDeep learning (3)Machine learning (3)Computer vision (1)Convolutional networks (1)Function approximation (1)Medical imaging (1)ML@GT (1)Pixel level inference (1)Probability estimation (1)PyTorch (1)... View MoreDate Issued
    2017 (5)
    Has File(s)Yes (5)
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