9 citations · 24 across the 15 of their papers we have counts for
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cs.LG2026
ConTex: Reformulating Counterfactual Generation For Time Series Forecasting
Jan Voets, Hasan Tercan, Tobias Meisen +1
Decision-making with deep learning-based time series forecasting requires not only accurate predictions but also actionable insights. However, current architectures do not inherent…
cs.LG2026
EXCODER: EXplainable Classification Of DiscretE time series Representations
Yannik Hahn, Antonin Königsfeld, Hasan Tercan +1
Deep learning has significantly improved time series classification, yet the lack of explainability in these models remains a major challenge. While Explainable AI (XAI) techniques…