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# Gated Recurrent Unit

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  1. medRxiv

    Interventional cardiac MRI at 10 radial spokes per frame: KOSTAL reconstructs in under 34 ms at the quality of 7 to 11 times more sampling

    Interventional cardiac MRI needs reconstruction latency below 200 ms, while high image quality usually demands more sampling. KOSTAL places a recurrent network directly on undersampled golden-angle radial k-space, using the sampling mask to decide at each location whether to keep accumulated data or take the new spokes, then refines once in image space. On simulated OCMR data, 10-spoke frames reached a median SSIM of 0.907 versus 0.622 for 10-spoke gridding, in under 34 ms per frame.

    Rady Children's Hospital-San DiegoUniversity of California San Diego
    Mark Buckup（First author）Francisco J. Contijoch（Corresponding author）
    KOSTALGated Recurrent UnitCardiac cine MRI reconstruction
  2. arXiv

    Recurrent memory no longer needs training: frozen networks recall over 256 steps with half the trainable parameters

    In partially observable reinforcement learning, freezing the recurrent memory module and training only the output and mixer layers still matches fully trained counterparts on delayed recall, discrete and continuous control, and pixel-based tasks, while cutting trainable parameters by more than half.

    University of Macau
    Zekang Wang（First author）
    Frozen Recurrent NetworkReservoir ComputingPartially Observable Markov Decision ProcessReinforcement LearningGated Recurrent Unit

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