Introduces M-information as a scalable measure of higher-order information integration in multivariate time series, computed via convex optimization and tested on neuronal and neuroimaging data.
Macroeconomics and reality,
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Hybrid KAN+XGBoost model outperforms SARIMAX, LSTM, standalone KAN and XGBoost on week-ahead electricity price forecasting in the Australian NEM, cutting MAE by ~12% versus XGBoost and over 50% versus naive baseline.
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A scalable estimator of higher-order information in complex dynamical systems
Introduces M-information as a scalable measure of higher-order information integration in multivariate time series, computed via convex optimization and tested on neuronal and neuroimaging data.
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Hybrid Kolmogorov-Arnold Network and XGBoost Framework for Week-Ahead Price Forecasting in Australia's National Electricity Market
Hybrid KAN+XGBoost model outperforms SARIMAX, LSTM, standalone KAN and XGBoost on week-ahead electricity price forecasting in the Australian NEM, cutting MAE by ~12% versus XGBoost and over 50% versus naive baseline.