Deep Confidence: A Computationally Efficient Framework for Calculating Reliable Prediction Errors for Deep Neural Networks

Published 2018 View Full Article

  1. Home
  2. Publications
  3. Publication Search
  4. Publication Details
Title
Deep Confidence: A Computationally Efficient Framework for Calculating Reliable Prediction Errors for Deep Neural Networks
Authors
Keywords
-
Journal
Journal of Chemical Information and Modeling
Volume -, Issue -, Pages -
Publisher
American Chemical Society (ACS)
Online
2018-10-18
DOI
10.1021/acs.jcim.8b00542

Ask authors/readers for more resources

Protocol

Community support

Reagent

Community support

Reprint

Contact the author

Discover Peeref hubs

Discuss science. Find collaborators. Network.

Join a conversation

Add your recorded webinar

Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.

Upload Now
Webinars Posters Questions Hubs Funding Journals Articles Connect Collections Reviewers About Us FAQs Mobile App Privacy Policy Terms of Use
© Peeref 2019-2024. All rights reserved.