1 citations · 1 across the 12 of their papers we have counts for
13 papers
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…
Advanced Global Wildfire Activity Modeling with Hierarchical Graph ODE
Fan Xu, Wei Gong, Hao Wu +6
Wildfires, as an integral component of the Earth system, are governed by a complex interplay of atmospheric, oceanic, and terrestrial processes spanning a vast range of spatiotempo…
NeuralOGCM: Differentiable Ocean Modeling with Learnable Physics
Hao Wu, Yuan Gao, Fan Xu +4
High-precision scientific simulation faces a long-standing trade-off between computational efficiency and physical fidelity. To address this challenge, we propose NeuralOGCM, an oc…
Unlocking Out-of-Distribution Generalization in Dynamics through Physics-Guided Augmentation
Fan Xu, Hao Wu, Kun Wang +5
In dynamical system modeling, traditional numerical methods are limited by high computational costs, while modern data-driven approaches struggle with data scarcity and distributio…
Breaking the Discretization Barrier of Continuous Physics Simulation Learning
Fan Xu, Hao Wu, Nan Wang +4
The modeling of complicated time-evolving physical dynamics from partial observations is a long-standing challenge. Particularly, observations can be sparsely distributed in a seem…
Spatiotemporal Forecasting as Planning: A Model-Based Reinforcement Learning Approach with Generative World Models
Hao Wu, Yuan Gao, Xingjian Shi +9
To address the dual challenges of inherent stochasticity and non-differentiable metrics in physical spatiotemporal forecasting, we propose Spatiotemporal Forecasting as Planning (S…