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Hao Hu

2 papers indexed

arxivcs.LG2026-07-05

Exogenous Dropout: A Simple, Strong Baseline for Corruption-Robust Time Series Forecasting with Covariates

Hao Hu, Xue-shan Ai

Time series forecasters that use exogenous covariates are fragile in deployment: when those covariates are noised, temporally misaligned, or missing, strong exogenous-fusion and exogenous-adapted models can degrade far above the endogenous-only floor. We study whether such robust…

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crossrefJournal of Marine Science and Engineering2025-04-08Cited by 12

Machine Learning in Maritime Safety for Autonomous Shipping: A Bibliometric Review and Future Trends

Jie Xue, Peijie Yang, Qianbing Li, Yuanming Song, P. H. A. J. M. van Gelder, Eleonora Papadimitriou, et al.

Autonomous vessels are becoming paramount to ocean transportation, while they also face complex risks in dynamic marine environments. Machine learning plays a crucial role in enhancing maritime safety by leveraging its data analysis and predictive capabilities. However, there has…

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