AAAI 2026technical0 citations
NeuralOM: Neural Ocean Model for Subseasonal-to-Seasonal Simulation
Yuan Gao, Hao Wu, Fan Xu, Yanfei Xiang, Ruijian Gou, Ruiqi Shu, Qingsong Wen, Xian Wu
Abstract
Long-term, high-fidelity simulation of slow-changing physical systems, such as the ocean and climate, presents a fundamental challenge in scientific computing. Traditional autoregressive machine learning models often fail in these tasks as minor errors accumulate and lead to rapid forecast degradation. To address this problem, we propose NeuralOM, a general neural operator framework designed for simulating complex, slow-changing dynamics. NeuralOM
BibTeX
@inproceedings{aaai2026_neuralomneuraloc,
title = {NeuralOM: Neural Ocean Model for Subseasonal-to-Seasonal Simulation},
author = {Yuan Gao and Hao Wu and Fan Xu and Yanfei Xiang and Ruijian Gou and Ruiqi Shu and Qingsong Wen and Xian Wu and Kun Wang and Xiaomeng Huang},
booktitle = {AAAI 2026},
year = {2026}
}