A two-level GNN with temperature sampling inside a Generate-and-Verify loop synthesizes enforceable, system-schedulable JLDs for cause-effect chains faster and more successfully than the prior greedy heuristic.
u nzel, Harun Teper, Georg von der Br\
1 Pith paper cite this work, alongside 5 external citations. Polarity classification is still indexing.
1
Pith paper citing it
5
external citations · OpenAlex
fields
cs.SE 1years
2026 1verdicts
ACCEPT 1representative citing papers
citing papers explorer
-
Schedulable Job-Level Dependencies for Cause-Effect Chains via Graph Neural Networks
A two-level GNN with temperature sampling inside a Generate-and-Verify loop synthesizes enforceable, system-schedulable JLDs for cause-effect chains faster and more successfully than the prior greedy heuristic.