Papers › Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity
Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity
Yunsheng Bai, Hao Ding, Yang Qiao, Agustin Marinovic, Ken Gu, Ting Chen, Yizhou Sun, Wei Wang
We introduce a novel approach to graph-level representation learning, which is to embed an entire graph into a vector space where the embeddings of two graphs preserve their graph-graph proximity. Our approach, UGRAPHEMB, is a general framework that provides a novel means to performing graph-level embedding in a completely unsupervised and inductive manner. The learned neural network can be considered as a function that receives any graph as input, either seen or unseen in the training set, and transforms it into an embedding. A novel graph-level embedding generation mechanism called Multi-Scale Node Attention (MSNA), is proposed. Experiments on five real graph datasets show that UGRAPHEMB achieves competitive accuracy in the tasks of graph classification, similarity ranking, and graph visualization.
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Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Graph Classification | IMDb-M | UGraphEmb-F | Accuracy | 50.97% | #17 of 36 | Archive leaderboard | report |
| Graph Classification | IMDb-M | UGraphEmb | Accuracy | 50.06% | #23 of 36 | Archive leaderboard | report |
| Graph Classification | NCI109 | UGraphEmb-F | Accuracy | 74.48 | #29 of 38 | Archive leaderboard | report |
| Graph Classification | NCI109 | UGraphEmb | Accuracy | 69.17 | #36 of 38 | Archive leaderboard | report |
| Graph Classification | PTC | UGraphEmb-F | Accuracy | 73.56% | #5 of 37 | Archive leaderboard | report |
| Graph Classification | PTC | UGraphEmb | Accuracy | 72.54% | #10 of 37 | Archive leaderboard | report |
| Graph Classification | REDDIT-MULTI-12K | UGraphEmb-F | Accuracy | 41.84 | #2 of 3 | Archive leaderboard | report |
| Graph Classification | REDDIT-MULTI-12K | UGraphEmb | Accuracy | 39.97 | #3 of 3 | Archive leaderboard | report |
| Graph Classification | Web | UGraphEmb-F | Accuracy | 45.03 | #1 of 1 | Archive leaderboard | report |
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