NVExplain: Explaining Time Series Forecasting with Latent Trajectory Analysis and Structure-Preserving Surrogates
A model-agnostic explainability framework that explains forecasting predictions by attributing each forecast horizon to temporally relevant historical lags is proposed, and results show that the semantic-flow variant achieves competitive or superior faithfulness compared to standard post-hoc baselines, while being subs...