arXiv Machine Learning By Huu Hiep Nguyen, Minh Hoang Nguyen, Dung Nguyen, Hung Le

Spectral Retrieval-Augmented Time-Series Forecasting

Read the original on arXiv Machine Learning →

arXiv:2606. 19412v1 Announce Type: new Abstract: Time series forecasting leverages historical patterns to predict future values, but traditional methods face challenges when dealing with complex, non-stationary patterns that are difficult to memorize during training.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

arXiv Machine Learning
Jun 4

Stationarity-Aware Retrieval-Augmented Time Series Forecasting

arXiv:2606. 04135v1 Announce Type: new Abstract: Time series forecasting relies on historical patterns, but real-world series often exhibit non-stationarity and regime shifts that challenge fully parametric forecasters.

By Shiqiao Zhou, Holger Sch\"oner, Zipeng Wu, Edouard Fouch\'e, IAG Wilson, Shuo Wang