This is the Linux app named Bootstrap Your Own Latent (BYOL) whose latest release can be downloaded as 0.7.0.zip. It can be run online in the free hosting provider OnWorks for workstations.
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SCREENSHOTS:
Bootstrap Your Own Latent (BYOL)
DESCRIPTION:
Practical implementation of an astoundingly simple method for self-supervised learning that achieves a new state-of-the-art (surpassing SimCLR) without contrastive learning and having to designate negative pairs. 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.
Features
- Practical implementation of an astoundingly simple method
- Group norm + weight standardization
- Simply plugin your neural network
- BYOL does not even need the target encoder to be an exponential moving average of the online encoder
- Fetch the embeddings or the projections
- Without contrastive learning
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/bootstrap-latent-byol.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.