Deep graph neural networks for link prediction
Graph neural networks (GNNs) is a form of machine learning architecture that uses many neurons to learn a given information which is similar to how a human brain works. It is also known as deep GNNs when there are many layers of information processing within the neural network architecture. GNNs...
Saved in:
Main Author: | Zheng, MingXi |
---|---|
Other Authors: | Tay Wee Peng |
Format: | Final Year Project |
Language: | English |
Published: |
Nanyang Technological University
2024
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/177145 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Pre-training graph neural networks for link prediction in biomedical networks
by: Long, Yahui, et al.
Published: (2022) -
Topic-aware heterogeneous graph neural network for link prediction
by: XU, Siyong, et al.
Published: (2021) -
App for predicting cryptocurrency price fluctuations with neural networks
by: Ho, Tristan Yue Ming
Published: (2024) -
Pre-training graph neural networks for link prediction in biomedical networks
by: LONG, Yahui, et al.
Published: (2022) -
Applying graph neural network to multivariate time series anomaly detection
by: Mao, Yiyun
Published: (2024)