Causal Discovery Evaluation Framework in the Absence of Ground-Truth Causal Graph
In causal learning, discovering the causal graph of the underlying generative mechanism from observed data is crucial. However, real-world data for causal discovery is scarce and expensive, leading researchers to rely on synthetic datasets, which may not accurately reflect real-world performance. To...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10669554/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|