arXiv Machine Learning June 15, 2026 By Fulong Yao, Wanqing Zhao, Chao Zheng, Xiaofei Han

Trend-Aware Multi-Task Learning for Short-Term Energy Forecasting

Read the original on arXiv Machine Learning →

arXiv:2511. 09789v3 Announce Type: replace Abstract: Short-term energy forecasting plays an important role in real-time operational decision-making, such as electricity market bidding and power system dispatch, where both numerical accuracy and correct directional signals are essential.

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

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CaReTS: A Multi-Task Framework Unifying Classification and Regression for Time Series Forecasting

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