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cs.LG2025
Learnable-Differentiable Finite Volume Solver for Accelerated Simulation of Flows
Mengtao Yan, Qi Wang, Haining Wang +7
Simulation of fluid flows is crucial for modeling physical phenomena like meteorology, aerodynamics, and biomedicine. Classical numerical solvers often require fine spatiotemporal…
cs.LG2025★ 1 cited
Conservation-informed Graph Learning for Spatiotemporal Dynamics Prediction
Yuan Mi, Pu Ren, Hongteng Xu +6
Data-centric methods have shown great potential in understanding and predicting spatiotemporal dynamics, enabling better design and control of the object system. However, deep lear…
cs.LG2024
Spatiotemporal Graph Learning with Direct Volumetric Information Passing and Feature Enhancement
Yuan Mi, Qi Wang, Xueqin Hu +4
Data-driven learning of physical systems has kindled significant attention, where many neural models have been developed. In particular, mesh-based graph neural networks (GNNs) hav…