Gradient boosted graph convolutional network on heterophilic graph

• Main Author: Seah, Ming Yang
• Other Authors: Tay Wee Peng
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2024
• Subjects: Engineering; Gradient; Boosting; Convolutional
• Online Access: https://hdl.handle.net/10356/176770
• Institution: Nanyang Technological University

Graph Neural Networks (GNNs) are impressive models that have been highly successful in performing graphical analysis and learning. However, GNNs are known to be outstanding in learning from homophilic graphs but are subpar in learning from heterophilic graphs. On the other hand, Gradient Boosted Dec...