A texture-geometry segmentation model feeding an autoregressive forecaster with structural memory predicts bacterial swarming front dynamics more stably than standard video-prediction networks.
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From shape to fate: making bacterial swarming expansion predictable
A texture-geometry segmentation model feeding an autoregressive forecaster with structural memory predicts bacterial swarming front dynamics more stably than standard video-prediction networks.