C.3: Locally Private Graph Neural Networks: Difference between revisions

From Circular Twain - Reference Implementations Wiki
Jump to navigationJump to search
No edit summary
No edit summary
Line 10: Line 10:
• '''Application in relevant Projects/Initiatives''': AI4Media
• '''Application in relevant Projects/Initiatives''': AI4Media


• '''AssetType''': Jupyter Notebook
• '''Asset Type''': Jupyter Notebook


• '''AI Breadth''': N.A.
• '''AI Breadth''': N.A.

Revision as of 10:27, 27 December 2024

Short Description: Federated training of Graph Neural Networks (GNNs) with Local Differential Privacy,  The code repository contains a python script, which can be used to train locally private GNNs, and a notebook to demonstrate the results.

Reference, URL: https://www.ai4europe.eu/research/ai-catalog/locally-private-graph-neural-networks

Applicable Business Category: Research (Cloud, Edge and Infrastructure)

Application in relevant Projects/Initiatives: AI4Media

Asset Type: Jupyter Notebook

AI Breadth: N.A.

Learning Ability: Graph Neural Networks

Related technologies:

Applicable Research Area: Collaborative AI, Verifiable AI

Applicable Technical Category: AI Ethics, Machine Learning

License Information: MIT license (MIT)

Related to circularity and sustainability: Yes

Audience: Developers



Go back to the AI portfolio of reference implementations