AIBullisharXiv – CS AI · 9h ago7/10
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Your GFlowNet Secretly Learns an Optimal Transport Plan
Researchers establish a theoretical connection between Generative Flow Networks (GFlowNets) and optimal transport theory, demonstrating that minimum-flow GFlowNets reduce to Kantorovich optimal transport problems. This framework enables GFlowNets to learn optimal transport plans on large graphs through neural parameterization, with experimental validation confirming alignment with exact solvers.