Inductive Representation Learning on Large Graphs

Low-dimensional embeddings of nodes in large graphs have proved extremely useful in a variety of prediction tasks, from content recommendation to identifying protein functions. However, most existing approaches require that all nodes in the graph are present during training of the embeddings; these previous approaches are inherently transductive and do not naturally generalize to unseen nodes... (read more)

PDF Abstract NeurIPS 2017 PDF NeurIPS 2017 Abstract

Datasets


Introduced in the Paper:

Reddit

Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT BENCHMARK
Node Classification Brazil Air-Traffic GraphSAGE (Hamilton et al., [2017a]) Accuracy 0.404 # 6
Graph Classification CIFAR10 100k GraphSage Accuracy (%) 66.08 # 4
Node Classification CiteSeer (0.5%) GraphSAGE Accuracy 33.8% # 15
Node Classification CiteSeer (1%) GraphSAGE Accuracy 51.0% # 13
Node Classification Citeseer Full-supervised GraphSAGE Accuracy 71.40% # 6
Node Classification CiteSeer with Public Split: fixed 20 nodes per class GraphSAGE Accuracy 67.2% # 20
Node Classification Cora (0.5%) GraphSAGE Accuracy 37.5% # 14
Node Classification Cora (1%) GraphSAGE Accuracy 49.0% # 12
Node Classification Cora (3%) GraphSAGE Accuracy 64.2% # 13
Node Classification Cora Full-supervised GraphSAGE Accuracy 82.20% # 6
Node Classification Cora with Public Split: fixed 20 nodes per class GraphSAGE Accuracy 74.5% # 25
Node Classification PATTERN 100k GraphSage Accuracy (%) 50.516 # 9
Node Classification PPI GraphSAGE F1 61.2 # 16
Node Classification PubMed (0.03%) GraphSAGE Accuracy 45.4% # 14
Node Classification PubMed (0.05%) GraphSAGE Accuracy 53.0% # 13
Node Classification PubMed (0.1%) GraphSAGE Accuracy 65.4% # 12
Node Classification Pubmed Full-supervised GraphSAGE Accuracy 87.10% # 6
Node Classification PubMed with Public Split: fixed 20 nodes per class GraphSAGE Accuracy 76.8% # 23
Node Classification Reddit GraphSAGE Accuracy 94.32% # 7
Graph Regression ZINC-500k GraphSage MAE 0.398 # 12

Results from Other Papers


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK SOURCE PAPER COMPARE
Node Classification Europe Air-Traffic GraphSAGE (Hamilton et al., [2017a]) Accuracy 27.2 # 6
Node Classification Facebook GraphSAGE (Hamilton et al., [2017a]) Accuracy 38.9 # 5
Node Classification Flickr GraphSAGE (Hamilton et al., [2017a]) Accuracy 0.641 # 2
Node Classification USA Air-Traffic GraphSAGE (Hamilton et al., [2017a]) Accuracy 31.6 # 6
Node Classification Wiki-Vote GraphSAGE (Hamilton et al., [2017a]) Accuracy 24.5 # 6

Methods used in the Paper


METHOD TYPE
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