The failures of marginal influence-based attribution methods for global time series explanations
Read the original at arxiv.org→arXiv:2607.16236v1 Announce Type: new Abstract: Explainability methods for time series models predominantly produce flat attribution scores: they quantify the direct influence of a feature at a timestamp by a...
Original headline: "The Failures of Marginal Influence-Based Attribution Methods for Global Time Series Explanations"