1 citations · 1 across the 3 of their papers we have counts for
4 papers
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…
SlotPi: Physics-informed Object-centric Reasoning Models
Jian Li, Wan Han, Ning Lin +8
Understanding and reasoning about dynamics governed by physical laws through visual observation, akin to human capabilities in the real world, poses significant challenges. Current…
MultiPDENet: PDE-embedded Learning with Multi-time-stepping for Accelerated Flow Simulation
Qi Wang, Yuan Mi, Haoyun Wang +5
Solving partial differential equations (PDEs) by numerical methods meet computational cost challenge for getting the accurate solution since fine grids and small time steps are req…
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…