1 citations · 1 across the 3 of their papers we have counts for
4 papers
Towards Accurate Subgraph Similarity Computation via Neural Graph Pruning
Linfeng Liu, Xu Han, Dawei Zhou +1
Subgraph similarity search, one of the core problems in graph search, concerns whether a target graph approximately contains a query graph. The problem is recently touched by neura…
Stochastic Iterative Graph Matching
Linfeng Liu, Michael C. Hughes, Soha Hassoun +1
Recent works leveraging Graph Neural Networks to approach graph matching tasks have shown promising results. Recent progress in learning discrete distributions poses new opportunit…
Modeling Graph Node Correlations with Neighbor Mixture Models
Linfeng Liu, Michael C. Hughes, Li-Ping Liu
We propose a new model, the Neighbor Mixture Model (NMM), for modeling node labels in a graph. This model aims to capture correlations between the labels of nodes in a local neighb…
Non-Parametric Variational Inference with Graph Convolutional Networks for Gaussian Processes
Linfeng Liu, Liping Liu
Inference for GP models with non-Gaussian noises is computationally expensive when dealing with large datasets. Many recent inference methods approximate the posterior distribution…