Causality
Causal modeling is crucial to the effectiveness and trust of AI by ensuring that actions lead to intended outcomes. We study the inference of causal effects and relationships, as well as the application of causal thinking to out-of-distribution generalization, fairness, robustness, and explainability.
Our work
Tools + code
Publications
- 2021
- CLOUD 2021
- 2021
- SMDS 2021
- 2021
- CLOUD 2021
- 2021
- KDD 2021
- 2021
- ICML 2021
- 2021
- ICML 2021