AC-GATE is a lag-gated neural encoder that conditions lag-weight distributions on entity proxies to recover heterogeneous lags as structural model outputs in panel time series.
Lessons from three decades of IT productivity research: towards a better understanding of IT-induced productivity effects: S. Schweikl, R. Obermaier
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Discovering Entity-Conditioned Lag Heterogeneity: A Lag-Gated Neural Audit Framework for Panel Time Series
AC-GATE is a lag-gated neural encoder that conditions lag-weight distributions on entity proxies to recover heterogeneous lags as structural model outputs in panel time series.