SPATE encodes data via spike trains mapped to quantum phases, yielding stronger feature representations than angle or amplitude encoding on datasets like Blobs and Moons.
FL-QDSNNs: Federated learning with quantum dynamic spiking neural networks
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A quantum-enhanced spiking Q-network is reported to outperform classical, spiking, and quantum-dense baselines in small grid-world navigation, with gains that are small relative to the reported error bars.
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SPATE: Spiking-Phase Adaptive Temporal Encoding for Quantum Machine Learning
SPATE encodes data via spike trains mapped to quantum phases, yielding stronger feature representations than angle or amplitude encoding on datasets like Blobs and Moons.
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Q-SpiRL: Quantum Spiking Reinforcement Learning for Adaptive Robot Navigation
A quantum-enhanced spiking Q-network is reported to outperform classical, spiking, and quantum-dense baselines in small grid-world navigation, with gains that are small relative to the reported error bars.