Showing 2 open source projects for "norm"

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    MNE-Python

    MNE-Python

    Magnetoencephalography (MEG) and Electroencephalography EEG in Python

    Open-source Python package for exploring, visualizing, and analyzing human neurophysiological data. MNE-Python is an open-source Python package for exploring, visualizing, and analyzing human neurophysiological data such as MEG, EEG, sEEG, ECoG, and more. It includes modules for data input/output, preprocessing, visualization, source estimation, time-frequency analysis, connectivity analysis, machine learning, statistics, and more.
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    Bootstrap Your Own Latent (BYOL)

    Bootstrap Your Own Latent (BYOL)

    Usable Implementation of "Bootstrap Your Own Latent" self-supervised

    ...This repository offers a module that one can easily wrap any image-based neural network (residual network, discriminator, policy network) to immediately start benefitting from unlabelled image data. There is now new evidence that batch normalization is key to making this technique work well. A new paper has successfully replaced batch norm with group norm + weight standardization, refuting that batch statistics are needed for BYOL to work. Simply plugin your neural network, specifying (1) the image dimensions as well as (2) the name (or index) of the hidden layer, whose output is used as the latent representation used for self-supervised training.
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