From the 1 of 15 linked papers with an AI index.
15 papers
Ocean-E2E: Hybrid Physics-Based and Data-Driven Global Forecasting of Extreme Marine Heatwaves with End-to-End Neural Assimilation
Ruiqi Shu, Ruijian Gou, Yanfei Xiang +1
The paper introduces Ocean-E2E, a hybrid physics‑based and data‑driven framework that uses end‑to‑end neural data assimilation to forecast global extreme marine heatwaves up to 40…
PnP-Corrector: A Universal Correction Framework for Coupled Spatiotemporal Forecasting
Hao Wu, Fan Xu, Yuxu Lu +9
Coupled spatiotemporal forecasting is important for predicting the future evolution of multiple interacting dynamical systems, such as in climate models. However, existing methods…
Differential-Integral Neural Operator for Long-Term Turbulence Forecasting
Hao Wu, Yuan Gao, Fan Xu +5
Accurately forecasting the long-term evolution of turbulence represents a grand challenge in scientific computing and is crucial for applications ranging from climate modeling to a…
RoboAlign-R1: Distilled Multimodal Reward Alignment for Robot Video World Models
Hao Wu, Yuqi Li, Yuan Gao +10
Existing robot video world models are typically trained with low-level objectives such as reconstruction and perceptual similarity, which are poorly aligned with the capabilities t…
OMNIFLOW: A Physics-Grounded Multimodal Agent for Generalized Scientific Reasoning
Hao Wu, Yongheng Zhang, Yuan Gao +7
Large Language Models (LLMs) have demonstrated exceptional logical reasoning capabilities but frequently struggle with the continuous spatiotemporal dynamics governed by Partial Di…
NeuralOM: Neural Ocean Model for Subseasonal-to-Seasonal Simulation
Yuan Gao, Hao Wu, Fan Xu +7
Long-term, high-fidelity simulation of slow-changing physical systems, such as the ocean and climate, presents a fundamental challenge in scientific computing. Traditional autoregr…