POSEIDON

POSEIDON is a foundation model for PDEs trained with an All2All semigroup augmentation: exploiting time separability to extract O(T^2) training pairs from a single trajectory, which greatly improves data efficiency.

Use cases: Fine-tuning a pretrained operator on a new PDE family with few samples; benchmarking transfer across elliptic, parabolic, hyperbolic and mixed operators.