PDEformer-2: a versatile foundation model for two-dimensional partial differential equations
Partial differential equations (PDEs) are fundamental to modeling physical systems. Traditional PDE solvers are often computationally expensive. Neural operators require independent training for different PDEs, and tend to be data-greedy when adapted to new scenarios. To this end, we introduce PDEformer-2, a versatil...