19 citations · 19 across the 1 of their papers we have counts for
3 papers
cs.LG2019★ 19 cited
Unsupervised Inductive Graph-Level Representation Learning via Graph-Graph Proximity
Yunsheng Bai, Hao Ding, Yang Qiao +5
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-…
cs.LG2018
Convolutional Set Matching for Graph Similarity
Yunsheng Bai, Hao Ding, Yizhou Sun +1
We introduce GSimCNN (Graph Similarity Computation via Convolutional Neural Networks) for predicting the similarity score between two graphs. As the core operation of graph similar…
cs.LG2018
SimGNN: A Neural Network Approach to Fast Graph Similarity Computation
Yunsheng Bai, Hao Ding, Song Bian +3
Graph similarity search is among the most important graph-based applications, e.g. finding the chemical compounds that are most similar to a query compound. Graph similarity comput…