Work

Estimating Causal Effects using a Multi-task Deep Ensemble

Year: 2023

Type: article

Abstract: . Compared to multi-task GP, CMDE efficiently handles high-dimensional and multi-modal covariates and provides pointwise uncertainty estimates of causal effects. We evaluate our method across various types of datasets and tasks and find that CMDE outperforms state-of-the-art methods on a majority of these tasks.

Source: PubMed

DOI: 10.48550/arxiv.2301.11351

Authors: Jiang, Ziyang, Hou, Zhuoran, Liu, Yiling, Ren, Yiman, Li, Keyu, Carlson, David

Institutions: Duke University, Duke Medical Center, University of Michigan

Language: English

Topic: Advanced Causal Inference Techniques

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Institutes of Health, National Institute of Mental Health, National Institute of Biomedical Imaging and Bioengineering