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Shortest Paths Discovery in Uncertain Networks via Transfer Learning

Summary: Uncertain graphs with probabilistic edges: finding the most probable shortest path between node pairs. Presents a fast non-learning Phase 2 sampler and a transfer-learning based predictor that estimates path probabilities without costly simulations, achieving up to 5x–210x speedups and scalable cross-domain generalization. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6644
Venue
SIGMOD
Year
2023
Pagerank
4.427232e-05
Overall Rank
8,907 | 38.04%
DOI
10.1145/3589286

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Rank Citing Paper Year Venue Pagerank
10,083 GeoKGM: A Multimodal Large Language Model for Zero-Shot Knowledge Graph Completion in Geospatial Databases 2026 SIGMOD 4.1945683e-05
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