Skip to content

Navigation Menu

Sign in
Appearance settings

Search code, repositories, users, issues, pull requests...

Provide feedback

We read every piece of feedback, and take your input very seriously.

Saved searches

Use saved searches to filter your results more quickly

Sign up
Appearance settings

Has POT incorporated the entropy-regularized Wasserstein loss for multilabel classification tasks? #557

Unanswered
BarretBa asked this question in Q&A
Discussion options

The paper 'Learning with a Wasserstein Loss' introduces the entropy-regularized Wasserstein loss for multilabel classification tasks, but I couldn't find how to call this function. Is this functionality integrated into POT?

You must be logged in to vote

Replies: 1 comment

Comment options

the multilabel classification loss is actually entropic unbalanced Ot thta can be computed with:

https://pythonot.github.io/all.html#ot.sinkhorn_unbalanced2

You must be logged in to vote
0 replies
Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Category
Q&A
Converted from issue

This discussion was converted from issue #553 on November 03, 2023 12:24.

AltStyle によって変換されたページ (->オリジナル) /