Search to Fine-tune Pre-trained Graph Neural Networks for Graph-level Tasks

1 code implementation • 14 Aug 2023 • Zhili Wang, Shimin Di, Lei Chen, Xiaofang Zhou

Given a pre-trained GNN, we propose to search to fine-tune pre-trained graph neural networks for graph-level tasks (S2PGNN), which adaptively design a suitable fine-tuning framework for the given labeled data on the downstream task.

AutoGEL: An Automated Graph Neural Network with Explicit Link Information

1 code implementation • NeurIPS 2021 • Zhili Wang, Shimin Di, Lei Chen

However, existing AutoGNN works mainly adopt an implicit way to model and leverage the link information in the graphs, which is not well regularized to the link prediction task on graphs, and limits the performance of AutoGNN for other graph tasks.

Graph Classification Link Prediction +1