58 citations · 69 across the 6 of their papers we have counts for
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hep-ph2026
Efficient Event Generation for High-Multiplicity LHC Processes: An End-to-End GPU Workflow with Normalizing Flows
Enrico Bothmann, Joshua Isaacson, Claudius Krause +3
Producing very large unweighted event samples for high-multiplicity processes is limited by expensive matrix-element evaluations and low unweighting efficiencies. We present the fi…
hep-ph2026
Monte Carlo Event Generation with Continuous Normalizing Flows
Enrico Bothmann, Timo Janßen, Max Knobbe +2
We apply Continuous Normalizing Flows trained with the Flow Matching method to the problem of phase-space sampling in Monte Carlo event generation for high-energy collider physics.…