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PDEBench

Benchmark datasets of generic PDEs for scientific machine learning

Takamoto et al. (NEC Labs and University of Stuttgart) · General PDEs · Public: code, data

Data doi.org⁠Paper NeurIPS

1D, 2D and 3D generic PDEs (advection, Burgers, Darcy, compressible and incompressible Navier–Stokes, shallow water) with varied initial and boundary conditions and parameters, plus code and baselines.

Licence
CC BY 4.0
Access
DaRUS data repository
Cases
336 files

Used by

  1. Paper · PretrainingMPP — Multiple Physics Pretraining for Physical Surrogate Models

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