This is the official implementation of Link Level Implicit Graph Neural Networks (LIGCN).
- pytorch
- torch-geometric
- tqdm
- numpy
- sklearn
To run the synthetic experiments
python train_synthetic.py
The dataset is too big to be provided in this folder. Please first follow the instructions in Long Range Graph Benchmark and download the PCQM-Contact files. Then, put the raw
folder (containing train.pt
, valid.pt
, test.pt
) into ./data/pcqm-contact/raw
.
To run the molecular property prediction experiments
python train_pcqm.py
To run the KGC experiments
python train_kg.py --dataset <dataset name>
For example,
python train_kg.py --dataset GraIL-BM_WN18RR_v1 --out_bias --cuda
python train_kg.py --dataset GraIL-BM_fb237_v1 --cuda
python train_kg.py --dataset GraIL-BM_nell_v1 --cuda