QLIF-CAST uses single-qubit quantum states to simulate leaky integrate-and-fire spiking dynamics in a recurrent architecture, achieving 15.4% lower MSE than classical LIF and up to 94% faster convergence than QLSTM on weather and air quality benchmarks.
A quantum-inspired self-supervised network model for automatic segmentation of brain mr images,
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QLIF-CAST: Quantum Leaky-Integrate-and-Fire for Time-Series Weather Forecasting
QLIF-CAST uses single-qubit quantum states to simulate leaky integrate-and-fire spiking dynamics in a recurrent architecture, achieving 15.4% lower MSE than classical LIF and up to 94% faster convergence than QLSTM on weather and air quality benchmarks.