A condensed time-expanded network with O(n²μ) nodes and O(μmn) edges solves max flow over time with μ capacity changes in O(μ²n³m) time.
26 Michael Hamann and Ben Strasser
3 Pith papers cite this work, alongside 1,877 external citations. Polarity classification is still indexing.
3
Pith papers citing it
1,877
external citations · external index
representative citing papers
ReBaHFC refines PaToH outputs with the new HyperFlowCutter flow algorithm to deliver hypergraph bipartition quality close to KaHyPar and hMETIS while running an order of magnitude faster.
An MPNN-PPO agent with max aggregation and hub-exclusion curriculum outperforms betweenness-centrality heuristics on budgeted max-flow channel placement across real Lightning Network snapshots, and has been deployed in production.
citing papers explorer
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Brief announcement: A special case of maximum flow over time with network changes
A condensed time-expanded network with O(n²μ) nodes and O(μmn) edges solves max flow over time with μ capacity changes in O(μ²n³m) time.
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Evaluation of a Flow-Based Hypergraph Bipartitioning Algorithm
ReBaHFC refines PaToH outputs with the new HyperFlowCutter flow algorithm to deliver hypergraph bipartition quality close to KaHyPar and hMETIS while running an order of magnitude faster.
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MPFlow: Learning Budgeted Max-Flow Optimization on the Lightning Network with Deep Graph Reinforcement Learning
An MPNN-PPO agent with max aggregation and hub-exclusion curriculum outperforms betweenness-centrality heuristics on budgeted max-flow channel placement across real Lightning Network snapshots, and has been deployed in production.