arXiv:2606. 01498v1 Announce Type: cross Abstract: Time series data inform critical decisions across many real-world domains.
Summary generated by The Flow from the publisher's feed. The full article lives at arXiv AI.
arXiv:2606. 05404v1 Announce Type: cross Abstract: Time series are often embedded in rich contexts that are essential for holistic modeling.
arXiv:2608. 14270v1 Announce Type: new Abstract: Time series analysis in high-stakes domains relies on recurring data releases, where new observations can alter the evidence base and the validity of later conclusions.
arXiv:2509. 11575v3 Announce Type: replace Abstract: Time series reasoning treats time as a first-class axis and incorporates intermediate evidence directly into the answer.
arXiv:2606. 15107v1 Announce Type: new Abstract: Time series data in real-world deployments is overwhelmingly irregular.
arXiv:2608. 03031v1 Announce Type: new Abstract: Time series forecasting is fundamental to decision-making in complex systems, where future dynamics are influenced not only by historical observations but also by evolving contextual features.
arXiv:2506. 10630v3 Announce Type: replace-cross Abstract: To advance time series forecasting (TSF), various methods have been proposed to improve prediction accuracy, evolving from statistical techniques to data-driven deep learning architectures.