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
Publications
- 2023
- WACV 2023
- 2022
- Big Data 2022
- 2022
- PLoS ONE
- 2021
- CLOUD 2021
- 2021
- SMDS 2021
- 2021
- CLOUD 2021