3.7k citations · 3.8k across the 13 of their papers we have counts for
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Learning Scalable Structural Representations for Link Prediction with Bloom Signatures
Tianyi Zhang, Haoteng Yin, Rongzhe Wei +2
Graph neural networks (GNNs) have shown great potential in learning on graphs, but they are known to perform sub-optimally on link prediction tasks. Existing GNNs are primarily des…
On the Inherent Privacy Properties of Discrete Denoising Diffusion Models
Rongzhe Wei, Eleonora Kreačić, Haoyu Wang +4
Privacy concerns have led to a surge in the creation of synthetic datasets, with diffusion models emerging as a promising avenue. Although prior studies have performed empirical ev…
OCTAL: Graph Representation Learning for LTL Model Checking
Prasita Mukherjee, Haoteng Yin
Model Checking is widely applied in verifying the correctness of complex and concurrent systems against a specification. Pure symbolic approaches while popular, suffer from the sta…
SUREL+: Moving from Walks to Sets for Scalable Subgraph-based Graph Representation Learning
Haoteng Yin, Muhan Zhang, Jianguo Wang +1
Subgraph-based graph representation learning (SGRL) has recently emerged as a powerful tool in many prediction tasks on graphs due to its advantages in model expressiveness and gen…