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Overcome the scalability bottleneck of GNN-based root cause analysis in edge computing by cascading subnetworks over clustered service graphs, achieving near-constant inference latency without sacrificing accuracy.
Optimizing UAV routes and edge computing together slashes wildfire monitoring response times by up to 84% while shrinking drone fleets by over 40%.
Circuit cutting introduces substantial end-to-end overheads in quantum neural network training, with reconstruction dominating per-query time, but surprisingly, test accuracy and robustness can be preserved or even improved.
