Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-06-28T17:59:27.746095Z
Paper Citation Record · LEDGER
As of 14 August 2026, this Paper Citation Record lists 80 of 80 outbound references and 0 inbound Pith citation observations for arXiv:2606.00949.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-06-28T17:59:27.746095Z
One-hop event checks from named stored sources.
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Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
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80 of 80 outbound references displayed
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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Brunton, S
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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction The autonomous cycle of near-wall turbulence , journal =
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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Coherent structures in wall-bounded turbulence , journal =
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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Rabault, J
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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Rabault, J
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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Flow control of three-dimensional cylinders transitioning to turbulence via multi-agent reinforcement learning , journal =
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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Hoyas, S
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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Hoyas, S
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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Hoyas, S
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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Cremades, A
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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction arXiv preprint arXiv:2601.05525 , year=
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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Rabault, J
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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Vinuesa, R
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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Rabault, J
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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Matteucci, L
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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction An Explainable Deep Learning for Data-Driven Turbulence Model Feature Discovery , year=
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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Benedikt, N
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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Explainable deep learning reveals the physical mechanisms behind the turbulent kinetic energy equation , journal =
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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction The minimal flow unit in near-wall turbulence , journal =
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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction and Cremades, A
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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Causal features in turbulent channel flow , journal =
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Reference 43
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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Reynolds -number dependence of turbulent skin-friction drag reduction induced by spanwise forcing
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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Effective control of two-dimensional Rayleigh–Bénard convection: Invariant multi-agent reinforcement learning is all you need.Physics of Fluids, 35(6):065146, June 2023
Reference 58
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Reference 59
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Reference 60
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Reference 61
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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Deep reinforcement learning for turbulent drag reduction in channel flows.The European Physical Journal E, 46(4):27, April 2023
Reference 62
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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Reinforcement learning of control strategies for reducing skin friction drag in a fully developed turbulent channel flow.Journal of Fluid Mechanics, 960:A30, April 2023
Reference 63
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Reference 64
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Reference 66
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Explainable deep reinforcement learning reveals energy-efficient control strategies for turbulent drag reduction Multiscale analysis of the topological invariants in the logarithmic region of turbulent channels at a friction Reynolds number of 932
Reference 68
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Reference 74
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Reference 75
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Reference 76
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Reference 80
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