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Found 3 papers, 0 papers with code
Unisolver: PDE-Conditional Transformers Are Universal PDE Solvers
Inspired by the mathematical structure of PDEs, we define a complete set of PDE components and correspondingly embed them as domain-wise (e. g. equation symbols) and point-wise (e. g. boundaries) conditions for Transformer PDE solvers.
RoPINN: Region Optimized Physics-Informed Neural Networks
To mitigate this inherent deficiency of the default scatter-point optimization, this paper proposes and theoretically studies a new training paradigm as region optimization.
HelmFluid: Learning Helmholtz Dynamics for Interpretable Fluid Prediction
Compared with previous velocity estimating methods, HelmFluid is faithfully derived from Helmholtz theorem and ravels out complex fluid dynamics with physically interpretable evidence.
