Search Results for author: Raquel Aoki

Found 4 papers, 3 papers with code

Causal Inference from Small High-dimensional Datasets

no code implementations19 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.

Causal Inference Transfer Learning

Multi-treatment Effect Estimation from Biomedical Data

1 code implementation14 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.

Multi-Task Learning

Heterogeneous Multi-task Learning with Expert Diversity

1 code implementation20 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.

Multi-Task Learning

ParKCa: Causal Inference with Partially Known Causes

1 code implementation17 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.

Association Causal Inference

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