Datasets:
File size: 1,978 Bytes
36110b6 c89b7bb 9fa1cbb 36110b6 9fa1cbb c89b7bb 9fa1cbb 6156b48 9fa1cbb c89b7bb 9fa1cbb 6156b48 9fa1cbb 6156b48 9fa1cbb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 | ---
license: apache-2.0
pretty_name: ICM Hyperelastic Dataset
task_categories:
- tabular-regression
tags:
- hyperelasticity
- mechanics
- plane-strain
- plane-stress
- finite-element
---
# ICM Hyperelastic Dataset
This dataset accompanies the paper:
https://arxiv.org/abs/2604.23098
The corresponding code is available at:
https://github.com/scaling-group/icm-hyperelastic
It contains compressed dataset archives used for training and evaluating models for hyperelastic material problems.
Because the data are provided as compressed `.tar.zst` archives, the Hugging Face Dataset Viewer is not available for this dataset.
## Dataset Splits
The archive names indicate the split and the mechanical setting:
| Name pattern | Meaning |
| --- | --- |
| `train` | Training set |
| `val105` | Test-ID |
| `val11` | Test-M |
| `val13D` | Test-MGL and Test-MGL+ |
| `pe` | Plane strain |
| `ps` | Plane stress |
For example:
- `dataset-train-pe.tar.zst`: training set under plane strain
- `dataset-train-ps.tar.zst`: training set under plane stress
- `dataset-val105-pe.tar.zst`: Test-ID under plane strain
- `dataset-val11-pe.tar.zst`: Test-M under plane strain
- `dataset-val13D-pe.tar.zst`: Test-MGL and Test-MGL+ under plane strain
## Usage Notes
Except for the experimental validation results, which use the plane-stress dataset for training, all other results in the paper use the plane-strain dataset.
In the file names:
- `pe` denotes plane strain.
- `ps` denotes plane stress.
## Citation
If you use this dataset, please cite the associated paper:
```bibtex
@article{li2026incontext,
title = {In-context modeling as a retrain-free paradigm for foundation models in computational science},
author = {Li, Lingfeng and Li, Zhuoyuan and Li, Shun and Zhan, Kaixin and Gao, Huajian and Chen, Changqing and Yang, Liu},
year = {2026},
url = {https://arxiv.org/abs/2604.23098},
eprint = {2604.23098},
archivePrefix = {arXiv},
primaryClass = {cs.CE}
}
```
|