Showing 1 open source project for "evidence"

View related business solutions
  • Try Google Cloud Risk-Free With $300 in Credit Icon
    Try Google Cloud Risk-Free With $300 in Credit

    No hidden charges. No surprise bills. Cancel anytime.

    Use your credit across every product. Compute, storage, AI, analytics. When it runs out, 20+ products stay free. You only pay when you choose to.
    Start Free
  • 8 Monitoring Tools in One APM. Install in 5 Minutes. Icon
    8 Monitoring Tools in One APM. Install in 5 Minutes.

    Errors, performance, logs, uptime, hosts, anomalies, dashboards, and check-ins. One interface.

    AppSignal works out of the box for Ruby, Elixir, Node.js, Python, and more. 30-day free trial, no credit card required.
    Start Free
  • 1
    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.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
MongoDB Logo MongoDB