no code implementations • 19 May 2022 • Raquel Aoki, Martin Ester
Our experiments show that such an approach helps to bring stability to neural network-based methods and improve the treatment effect estimates in small high-dimensional datasets.
1 code implementation • 14 Dec 2021 • Raquel Aoki, Yizhou Chen, Martin Ester
This work proposes the M3E2, a multi-task learning neural network model to estimate the effect of multiple treatments.
1 code implementation • 20 Jun 2021 • Raquel Aoki, Frederick Tung, Gabriel L. Oliveira
In contrast to single-task learning, in which a separate model is trained for each target, multi-task learning (MTL) optimizes a single model to predict multiple related targets simultaneously.
1 code implementation • 17 Mar 2020 • Raquel Aoki, Martin Ester
Methods for causal inference from observational data are an alternative for scenarios where collecting counterfactual data or realizing a randomized experiment is not possible.