66 citations · 94 across the 6 of their papers we have counts for
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cs.LG2025
Explainable time-series forecasting with sampling-free SHAP for Transformers
Matthias Hertel, Sebastian Pütz, Ralf Mikut +2
Time-series forecasts are essential for planning and decision-making in many domains. Explainability is key to building user trust and meeting transparency requirements. Shapley Ad…
cs.LG2025★ 2 cited
Real-E: A Foundation Benchmark for Advancing Robust and Generalizable Electricity Forecasting
Chen Shao, Yue Wang, Zhenyi Zhu +5
Energy forecasting is vital for grid reliability and operational efficiency. Although recent advances in time series forecasting have led to progress, existing benchmarks remain li…