A Gaussian process forecaster that uses decayed random Fourier signature features to weight recent time series observations more heavily, beating GP baselines and matching diffusion models on standard benchmarks.
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Learning to Forget: Bayesian Time Series Forecasting using Recurrent Sparse Spectrum Signature Gaussian Processes
A Gaussian process forecaster that uses decayed random Fourier signature features to weight recent time series observations more heavily, beating GP baselines and matching diffusion models on standard benchmarks.