A walk-based reinforcement sampler learns to extract important graph substructures for classification, matching or beating existing subgraph methods on seven benchmark datasets.
Protein function prediction via graph kernels
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Self-supervised Subgraph Neural Network With Deep Reinforcement Walk Exploration
A walk-based reinforcement sampler learns to extract important graph substructures for classification, matching or beating existing subgraph methods on seven benchmark datasets.