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Selective Transfer Learning for Groundwater Level Anomaly Forecasting: Accuracy-Risk Trade-offs
This work studies context-aware selective transfer learning for multi-well groundwater anomaly forecasting in the Netherlands. Source-domain pretraining can raise average accuracy but is not uniformly reliable: it degrades performance on a substantial fraction of heterogeneous wells. Context-Aware S
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