DeRegiME uses a sparse variational GP with nonstationary regime-mixing kernel to decompose forecasts into mean, residual regimes, and noise for improved probabilistic forecasting under distribution shift.
Proceedings of the AAAI Conference on Artificial Intelligence , volume =
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A single-layer GRU model using NASA Black Marble nightlights nowcasts Italian municipal taxable income with 1.07 million euro median error (4% of median), statistically outperforming persistence, fixed effects, ARDL, and spatial econometric benchmarks out-of-sample on 2020-2021.
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DeRegiME: Deep Regime Mixtures for Probabilistic Forecasting under Distribution Shift
DeRegiME uses a sparse variational GP with nonstationary regime-mixing kernel to decompose forecasts into mean, residual regimes, and noise for improved probabilistic forecasting under distribution shift.
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Nowcasting Italian Municipal Income with Nightlights: A Deep Learning Approach
A single-layer GRU model using NASA Black Marble nightlights nowcasts Italian municipal taxable income with 1.07 million euro median error (4% of median), statistically outperforming persistence, fixed effects, ARDL, and spatial econometric benchmarks out-of-sample on 2020-2021.