Yi-Shun Zhu

Experiments on long-horizon autoregressive ORAS5 forecasting show that OceanMoE lowers aggregate forecasting error and maintains lower geometric-mean normalized RMSE than the corresponding baselines over most later rollout months, which support structured conditional computation as a modeling strategy for balancing shared ocean context with adaptive specialization.