1 to 10 of 385 Results
Feb 13, 2024
Takamoto, Makoto; Praditia, Timothy; Leiteritz, Raphael; MacKinlay, Dan; Alesiani, Francesco; Pflüger, Dirk; Niepert, Mathias, 2022, "PDEBench Datasets", https://doi.org/10.18419/darus-2986, DaRUS, V8
This dataset contains benchmark data, generated with numerical simulation based on different PDEs, namely 1D advection, 1D Burgers', 1D and 2D diffusion-reaction, 1D diffusion-sorption, 1D, 2D, and 3D compressible Navier-Stokes, 2D Darcy flow, and 2D shallow water equation. This... |
Feb 13, 2024 -
PDEBench Datasets
Hierarchical Data Format - 7.7 GB -
MD5: e6d9a4f62baf9a29121a816b919e2770
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Feb 13, 2024 -
PDEBench Datasets
Hierarchical Data Format - 7.7 GB -
MD5: 16f4c7afaf8c16238be157e54c9297c7
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Feb 13, 2024 -
PDEBench Datasets
Hierarchical Data Format - 7.7 GB -
MD5: 9021eba35332d127306f11ef84c1a60f
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Feb 13, 2024 -
PDEBench Datasets
Hierarchical Data Format - 7.7 GB -
MD5: 70fe0c24d9313e70f6059e5212bdb3d7
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Nov 30, 2023
Takamoto, Makoto; Praditia, Timothy; Leiteritz, Raphael; MacKinlay, Dan; Alesiani, Francesco; Pflüger, Dirk; Niepert, Mathias, 2022, "PDEBench Pretrained Models", https://doi.org/10.18419/darus-2987, DaRUS, V2
This dataset contains the pretrained baseline models, namely FNO, U-Net, and PINN. These models are trained on different PDEs, such as 1D advection, 1D Burgers', 1D and 2D diffusion-reaction, 1D diffusion-sorption, 1D, 2D, and 3D compressible Navier-Stokes, 2D Darcy flow, and 2D... |
Nov 30, 2023 -
PDEBench Pretrained Models
Plain Text - 1.9 MB -
MD5: e80f6e427a3a47802969856ea1ce56b1
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Nov 30, 2023 -
PDEBench Pretrained Models
Plain Text - 1.1 MB -
MD5: 441102e4e3ee6cd725433d32fc2f78ed
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Nov 30, 2023 -
PDEBench Pretrained Models
Plain Text - 111.1 MB -
MD5: 7deebad46a2ea4eebfc1b297dd1ada08
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Nov 30, 2023 -
PDEBench Pretrained Models
Plain Text - 1.9 MB -
MD5: dccb09c3d0f93bf9508bcbc45ac1b8a6
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