Robust Graph Learning

This repository contains source code for the Robust Graph Learning project.

Data:

• DBLP
• Enron10
• Facebook
• Wikipedia: http://snap.stanford.edu/jodie/wikipedia.csv
• Reddit: http://snap.stanford.edu/jodie/reddit.csv

Attack:

We use DeepRobust to perform most attacks.
DeepRobust Documentation
Attack methods integrated in our framework:

• Random Attack
• Meta Attack
• Dice Attack
• Node Attack
• Temporal Attack (our own method)

Baseline:

Static GNNs:

• GAE: https://github.com/DaehanKim/vgae_pytorch
• VGAE: https://github.com/DaehanKim/vgae_pytorch

Discrete Dynamics GNNs:

• EvolveGCN (EGCN-H, EGCN-O): https://github.com/IBM/EvolveGCN
• Euler: https://github.com/iHeartGraph/Euler
• DySAT: https://github.com/FeiGSSS/DySAT_pytorch

Continuous Dynamics GNN:

• TGAT: https://github.com/StatsDLMathsRecomSys/Inductive-representation-learning-on-temporal-graphs

Static Defense GNN:

• Pro-GNN: https://github.com/ChandlerBang/Pro-GNN

Usage:

• Using config file to train: python3 entries/train.py --cfg ./configs/link_pred_temporal_dblp.yaml
• Overwrite config by args: python3 entries/train.py --help

train.py [-h] [--gpu GPU] [--device DEVICE] [--seed SEED] [--data_name [DATA_NAME]] [--data_dir [DATA_DIR]]     [--model_name MODEL_NAME]
                [--test_time_step TEST_TIME_STEP] [--input_feat INPUT_FEAT] [--batch_size BATCH_SIZE] [--emb_dim EMB_DIM] [--lr LR]
                [--max_epoch MAX_EPOCH] [--ptb_rate PTB_RATE] [--attack_method ATTACK_METHOD] [--stopping_steps STOPPING_STEPS]
                [--log_interval LOG_INTERVAL] [--evaluate_epoch EVALUATE_EPOCH] [--runs RUNS] [--cfg CFG] [--load LOAD] [--opts ...]
robust graph learning on dynamic graphs

optional arguments:
  -h, --help            show this help message and exit
  --gpu GPU             default is to use gpu
  --device DEVICE       device id
  --seed SEED           Random seed.
  --data_name [DATA_NAME]
                        Choose a dataset from {dblp, enron10, fb}
  --data_dir [DATA_DIR]
                        Input data path.
  --model_name MODEL_NAME
                        Model name
  --test_time_step TEST_TIME_STEP
                        number of test time steps
  --input_feat INPUT_FEAT
                        0: No pretrain, 1: Pretrain with the learned embeddings, 2: Pretrain with BERT.
  --batch_size BATCH_SIZE
                        recommendation batch size.
  --emb_dim EMB_DIM     node embedding size.
  --lr LR               Learning rate.
  --max_epoch MAX_EPOCH
                        Number of epoch.
  --ptb_rate PTB_RATE   attack rate.
  --attack_method ATTACK_METHOD
                        attack_func.
  --stopping_steps STOPPING_STEPS
                        Number of epoch for early stopping
  --log_interval LOG_INTERVAL
                        Iter interval of printing loss.
  --evaluate_epoch EVALUATE_EPOCH
                        Epoch interval of evaluation.
  --runs RUNS           Independent runs with different seeds.
  --cfg CFG             specify particular yaml configuration to use
  --load LOAD           specify saved checkpoint to evaluate
  --opts ...            Command line options to overwrite configs