Giter Site home page Giter Site logo

Dropout in last layer about powerful-gnns HOT 2 OPEN

weihua916 avatar weihua916 commented on June 15, 2024
Dropout in last layer

from powerful-gnns.

Comments (2)

weihua916 avatar weihua916 commented on June 15, 2024

It's just a regularization.

from powerful-gnns.

foxtrotmike avatar foxtrotmike commented on June 15, 2024

Thank you for your response - Tome, it makes sense to regularize using dropout at layers before the last one. Dropout at the prediction output forces prediction scores of an example to become zero and also scales up the prediction scores of other examples in the batch. Please see: "Furthermore, the outputs are scaled by a factor of \frac{1}{1-p}" in https://pytorch.org/docs/stable/generated/torch.nn.Dropout.html
It would be great if you could help me understand this a bit better. Thanks, again.

from powerful-gnns.

Related Issues (20)

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.