A tabular data generation framework guided by downstream tasks optimization
Abstract Recently, generative models have been gradually emerging into the extended dataset field, showcasing their advantages. However, when it comes to generating tabular data, these models often fail to satisfy the constraints of numerical columns, which cannot generate high-quality datasets that...
Saved in:
| Main Authors: | , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-07-01
|
| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-024-65777-9 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|