readme.md

JUST JUMP: DYNAMIC NEIGHBORHOOD AGGREGATION IN GRAPH NEURAL NETWORKS (DNA)

• Paper link: https://arxiv.org/abs/1904.04849
• The implementation of PyG: https://github.com/pyg-team/pytorch_geometric/blob/master/examples/dna.py.

Dataset Statics

Dataset	# Nodes	# Edges	# Classes
Cora	2,708	10,556	7
Citeseer	3,327	9,228	6
Pubmed	19,717	88,651	3

Refer to Planetoid.

Results

# available dataset: "cora", "citeseer", "pubmed"

TL_BACKEND="torch" python dna_trainer.py --dataset cora --lr 0.01 --drop_rate_conv 0.2 --drop_rate_model 0.8 --num_layers 3 --heads 64 --groups 1 --l2_coef 5e-5 --hidden_dim 256
TL_BACKEND="torch" python dna_trainer.py --dataset cora --lr 0.01 --drop_rate_conv 0.2 --drop_rate_model 0.9 --num_layers 3 --heads 32 --groups 8 --l2_coef 5e-5 --hidden_dim 256
TL_BACKEND="torch" python dna_trainer.py --dataset cora --lr 0.01 --drop_rate_conv 0.1 --drop_rate_model 0.8 --num_layers 4 --heads 8 --groups 16 --l2_coef 5e-5 --hidden_dim 128
TL_BACKEND="torch" python dna_trainer.py --dataset citeseer --lr 0.01 --drop_rate_conv 0.2 --drop_rate_model 0.8 --num_layers 3 --heads 32 --groups 1 --l2_coef 5e-5 --hidden_dim 128
TL_BACKEND="torch" python dna_trainer.py --dataset citeseer --lr 0.01 --drop_rate_conv 0.1 --drop_rate_model 0.8 --num_layers 4 --heads 8 --groups 8 --l2_coef 5e-5 --hidden_dim 128
TL_BACKEND="torch" python dna_trainer.py --dataset citeseer --lr 0.01 --drop_rate_conv 0.1 --drop_rate_model 0.8 --num_layers 4 --heads 8 --groups 16 --l2_coef 5e-5 --hidden_dim 128
TL_BACKEND="torch" python dna_trainer.py --dataset pubmed --lr 0.01 --drop_rate_conv 0.1 --drop_rate_model 0.8 --num_layers 4 --heads 8 --groups 1 --l2_coef 5e-5 --hidden_dim 128
TL_BACKEND="torch" python dna_trainer.py --dataset pubmed --lr 0.01 --drop_rate_conv 0.1 --drop_rate_model 0.8 --num_layers 4 --heads 8 --groups 8 --l2_coef 5e-5 --hidden_dim 128
TL_BACKEND="torch" python dna_trainer.py --dataset pubmed --lr 0.01 --drop_rate_conv 0.1 --drop_rate_model 0.8 --num_layers 4 --heads 8 --groups 16 --l2_coef 5e-5 --hidden_dim 128

Dataset	group	Paper	Our(th)
cora	1	83.88±0.50	80.50±0.81
cora	8	85.86±0.45	81.22±0.18
cora	16	86.15±0.57	82.25±0.4
citeseer	1	73.37±0.83	71.41±1.02
citeseer	8	74.19±0.66	72.29±0.59
citeseer	16	74.50±0.62	72.99±0.68
pubmed	1	87.80±0.25	87.32±0.52
pubmed	8	88.04±0.17	87.46±0.25
pubmed	16	88.04±0.22	87.49±0.11