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Bridging the gap between attribution and counterfactual explanations, this framework achieves unprecedented stability and reliability in time series model interpretability.
Achieving high-quality time series forecasting with just a few examples, MetaCaster revolutionizes the way lightweight forecasters are trained in data-scarce environments.
Faithful explanations in time series forecasting can be achieved without sacrificing accuracy, as IB-Forecast demonstrates superior performance over traditional interpretable models and black-box approaches.
