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    On deep learning in physics 

    Mills, Kyle (2021-04-01)
    Machine learning, and most notably deep neural networks, have seen unprecedented success in recent years due to their ability to learn complex nonlinear mappings by ingesting large amounts of data through the process of ...
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    An anomaly detection model utilizing attributes of low powered networks, IEEE 802.15.4e/TSCH and machine learning methods 

    Salgadoe, Sajeeva (2019-12-01)
    The rapid growth in sensors, low-power integrated circuits, and wireless communication standards has enabled a new generation of applications based on ultra-low powered wireless sensor networks. These are employed in many ...
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    A modular interface framework for multimodal annotations and visualizations in Human-AI collaboration 

    Kim, Chris (2021-07-01)
    Modular is a web-based annotation, visualization, and inference software plat-form for computational language and vision research. The platform enables researchers to set up an interface for efficiently annotating language ...

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    AuthorKim, Chris (1)Mills, Kyle (1)Salgadoe, Sajeeva (1)Subject
    Machine learning (3)
    Anomaly detection (1)Artificial intelligence (1)Deep learning (1)Deep neural networks (1)Human-computer interaction (1)IEEE 802.15.4e/TSCH (1)Interactive visualization (1)Knowledge representation (1)Materials science (1)... View MoreDate Issued2021 (2)2019 (1)Has File(s)Yes (3)

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