This repository contains a PyTorch implementation for our paper "HGOE: Hybrid External and Internal Graph Outlier Exposure for Graph Out-of-Distribution Detection".

Requirements

This code requires the following:

• Python==3.9
• Pytorch==1.11.0
• Pytorch Geometric==2.0.4
• Numpy==1.21.2
• Scikit-learn==1.0.2
• OGB==1.3.3
• NetworkX==2.7.1
• FAISS-GPU==1.7.2

Usage

Just run the script corresponding to the experiment and dataset you want. For instance:

Run out-of-distribution detection on AIDS (ID) and DHFR (OOD) datasets:

bash script/run_AIDS+DHFR.sh
bash script/run_ogbg-molesol+ogbg-molmuv.sh
bash script/run_ogbg-molfreesolv+ogbg-moltoxcast.sh
bash script/run_ogbg-moltox21+ogbg-molsider.sh
...