Estimating Causal Effects using a Multi-task Deep Ensemble

2023/01/26 by Ziyang Jiang, Zhuoran Hou, Jiang, Ziyang +9 · 2 citations
Computer Science · #Machine Learning in Healthcare #Gaussian Processes and Bayesian Inference #Bayesian Modeling and Causal Inference

paper · doi:10.48550/arxiv.2301.11351

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.

Cited by

• Observationally Informed Adaptive Causal Experimental Design
• Stochastic Neural Networks for Causal Inference with Missing Confounders

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