3 papers
cs.LG2026
Bounding the Causal Impact of ML-assisted Decision-Making via Counterfactual Correctness
Jonathan Zhang, Erik Skalnes, Jacob Chen +1
Predictive machine learning (ML) models are increasingly used to aid human decision-makers across various high-risk domains such as healthcare and criminal justice. There is a grow…
stat.ME2025
Just Trial Once: Ongoing Causal Validation of Machine Learning Models
Jacob M. Chen, Michael Oberst
Machine learning (ML) models are increasingly used as decision-support tools in high-risk domains. Evaluating the causal impact of deploying such models can be done with a randomiz…
cs.CL2024
Proximal Causal Inference With Text Data
Jacob M. Chen, Rohit Bhattacharya, Katherine A. Keith
Recent text-based causal methods attempt to mitigate confounding bias by estimating proxies of confounding variables that are partially or imperfectly measured from unstructured te…