AI RESEARCH
QLIF-CAST: Quantum Leaky-Integrate-and-Fire for Time-Series Weather Forecasting
arXiv CS.LG
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ArXi:2605.18333v1 Announce Type: cross Accurate and efficient time-series forecasting remains a challenging problem for both classical and quantum neural architectures, particularly in multivariate environmental settings. This work adapts the Quantum Leaky Integrate-and-Fire (QLIF) spiking neural network for time-series regression tasks, specifically short-term multivariate weather forecasting. We extend QLIF beyond classification and nstrate its applicability to continuous-valued prediction problems.