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arXiv cs.LG
arXiv cs.LG
5/12/2026
Path-Based Gradient Boosting for Graph-Level Prediction

Path-Based Gradient Boosting for Graph-Level Prediction

Short summary

PathBoost is a new gradient boosting method for graph-level classification that learns discriminative path-based features directly from structure. It matches or outperforms graph neural networks and graph kernels on benchmarks, with particular strength on larger graphs, and eliminates manual anchor node selection.

  • •Path-based gradient boosting method with automatic anchor node selection via categorical diversity
  • •Competitive or superior to GNNs and graph kernels; outperforms on half of benchmark datasets
  • •Particularly effective on graphs with larger average node counts

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