Meta learning for causal direction
The inaccessibility of controlled randomized trials due to inherent constraints in many fields of science has been a fundamental issue in causal inference. In this paper, we focus on distinguishing the cause from effect in the bivariate setting under limited observational data. Based on recent devel...
| Asıl Yazarlar: | , , |
|---|---|
| Materyal Türü: | Conference item |
| Dil: | English |
| Baskı/Yayın Bilgisi: |
Association for the Advancement of Artificial Intelligence
2021
|