This repository contains the implementation of the paper "Learning Gradients of Convex Functions with Monotone Gradient Networks". The paper introduces two new neural architectures that helps in learning gradient of convex functions. This has also an utility in optimal transport domain mainly the Brenier Map Theorem.
-
Notifications
You must be signed in to change notification settings - Fork 0
This repository contains the implementation of the paper "Learning Gradients of Convex Functions with Monotone Gradient Networks". The paper introduces two new neural architectures that helps in learning gradient of convex functions. This has also an utility in optimal transport domain mainly the Brenier Map Theorem.
midsougou/Learning-Gradient-of-Convex-Functions-Using-Neural-Network
Folders and files
| Name | Name | Last commit message | Last commit date | |
|---|---|---|---|---|
Repository files navigation
About
This repository contains the implementation of the paper "Learning Gradients of Convex Functions with Monotone Gradient Networks". The paper introduces two new neural architectures that helps in learning gradient of convex functions. This has also an utility in optimal transport domain mainly the Brenier Map Theorem.
Topics
Resources
Stars
Watchers
Forks
Releases
No releases published
Packages 0
No packages published