Data · dataset · 2023
PDEBench Pretrained Models
Listed in DaRUS
This dataset contains the pretrained baseline models, namely FNO, U-Net, and PINN.
Description
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 shallow water equation. In addition the dataset contains the pre-trained model for the 1D Inverse problem for FNO and U-Net.
These models are stored using the same structure as the dataset they trained on. All the files are saved in .pt files, the default file type for the PyTorch library. More detailed information are also provided in our Github repository (github.com/pdebench/PDEBench) and our submitting paper to NeurIPS 2022 Benchmark track.
Links
Where it is published
- Dataverse dataset page darus.uni-stuttgart.de/dataset.xhtml?persistentId=doi%3A10.18419%2FDARUS-2987 ↗
landing page · from darus uni stuttgart de
- DOI doi.org/10.18419/darus-2987 ↗
DOI / persistent id · from darus uni stuttgart de
Catalogue records · 1
- Dataverse API darus.uni-stuttgart.de/api/datasets/:persistentId/?persistentId=doi%3A10.18419%2FDARU… ↗
metadata API · from darus uni stuttgart de
Topics
- Stated by source
- Computer and Information Science · Earth and Environmental Sciences · Physics
- From keywords
- Computer Science & AI · Earth & Environmental Science · Machine learning · Physics
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| DaRUS | doi:10.18419/DARUS-2987 | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:4611 | mapping · darus uni stuttgart de | vocabulary-mapper@1.0.0 | keywords['Machine Learning'] |
| concepts[field].dataverse_subject:computer-and-information-science | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /subjects |
| concepts[field].dataverse_subject:earth-and-environmental-sciences | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /subjects |
| concepts[field].dataverse_subject:physics | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /subjects |
| concepts[field].local:field:computer-science-ai | mapping · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /subjects |
| concepts[field].local:field:earth-environmental | mapping · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /subjects |
| concepts[field].local:field:physics | mapping · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /subjects |
| created_date | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | |
| description | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /description |
| publication_date | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | |
| title | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | /name |
| updated_date | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 | |
| version_label | source · darus uni stuttgart de | connector:darus_uni_stuttgart_de@1.0.0 |