Graph Neural Networks: Message Passing and Applications

Status: public · Confidence: medium (0.78) · Basis: verified_sources

## TL;DR

Graph neural networks learn from relational structure such as nodes, edges, and neighborhoods. This repair avoids unsupported application claims and keeps the public facts to core methods.

## Core Explanation

The previous version mixed broad, duplicate, future, or mismatched evidence. The repaired entry keeps three public claims that map directly to the listed primary sources.

## Further Reading

- [Semi-Supervised Classification with Graph Convolutional Networks](https://arxiv.org/abs/1609.02907)
- [Graph Attention Networks](https://arxiv.org/abs/1710.10903)
- [Graph Representation Learning](https://www.cs.mcgill.ca/~wlh/grl_book/)