- Interpretable machine learning for heterogeneous treatment effect ...🔍
- tlverse/causalglm🔍
- Interpretable machine learning🔍
- Toward Interpretable and Precise Treatment Effect Estimation🔍
- Machine Learning for Treatment Effect Heterogeneity🔍
- Automated interpretable discovery of heterogeneous treatment ...🔍
- Machine Learning Based Estimation of Heterogeneous Treatment ...🔍
- Benchmarking Heterogeneous Treatment Effect Models through the ...🔍
Interpretable machine learning for heterogeneous treatment effect ...
Interpretable machine learning for heterogeneous treatment effect ...
Interpretable machine learning for heterogeneous treatment effect estimators with Double ML: a case of access to credit for SMEs · Abstract · Keywords.
Interpretable machine learning for heterogeneous treatment effect ...
Interpretable machine learning for heterogeneous treatment effect estimators with Double ML: a case of access to credit for SMEs. Kyrylo Medianovskyia ...
Interpretable machine learning for heterogeneous treatment effect ...
Interpretable machine learning for heterogeneous treatment effect estimators with Double ML: a case of access to credit for SMEs /. Authors, Medianovskyi ...
tlverse/causalglm: Interpretable and model-robust causal ... - GitHub
Interpretable and model-robust causal inference for heterogeneous treatment effects using generalized linear working models with targeted machine-learning ...
Interpretable machine learning for heterogeneous treatment effect ...
Request PDF | Interpretable machine learning for heterogeneous treatment effect estimators with Double ML: a case of access to credit for SMEs ...
Interpretable machine learning - van der Schaar Lab
Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability. Jonathan Crabbé, Alicia Curth, Ioana Bica, Mihaela van der Schaar
Toward Interpretable and Precise Treatment Effect Estimation - arXiv
Abstract:Understanding and inferencing Heterogeneous Treatment Effects (HTE) and Conditional Average Treatment Effects (CATE) are vital for ...
Machine Learning for Treatment Effect Heterogeneity
Recent developments in the causal inference literature introduced Machine Learning (ML) algorithms to the analysis of heterogeneous treatment effects.
CRE: An R package for interpretable discovery and inference of ...
causal inference heterogeneous effect interpretability machine learning. Altmetrics. Markdown badge. License. Authors of JOSS papers retain ...
Automated interpretable discovery of heterogeneous treatment ...
Keywords: COVID-19, Heterogeneous Treatment Effects, Personalized Medicine, Interpretable Machine Learning. Go to: Abstract. Testing multiple ...
Machine Learning Based Estimation of Heterogeneous Treatment ...
Machine Learning Based Estimation of Heterogeneous Treatment Effects ... One of the biggest promises of machine learning is the automation of decision making in ...
Benchmarking Heterogeneous Treatment Effect Models through the ...
Title:Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability ; Subjects: Machine Learning (cs.LG); Artificial ...
Detecting heterogeneous treatment effects with instrumental ...
In this work we present a method to estimate heterogeneous causal effects using an instrumental variable with matching.
Benchmarking Heterogeneous Treatment Effect Models through the ...
literature on learning treatment effect heterogeneity has emerged in machine learning (ML) ... Covariate-balancing-aware interpretable deep learning models for ...
AI and Causality: Estimating Heterogeneous Treatment Effects ...
Background: In recent years, artificial intelligence/machine learning (AI/ML) has seen important advances in its theoretical and practical ...
Automated Interpretable Discovery of Heterogeneous Treatment ...
... treatment effectiveness using multitask machine learning. In this paper, we present a method to estimate these heterogeneous treatment effects ...
8 Machine learning helps us analyze the impact of policies and ...
Machine learning methods can help us flexibly estimate heterogeneous treatment effects and choose an optimal policy for behavioral interventions.
Causal Rule Learning: Enhancing the Understanding of ...
Interpretability is a key concern in estimating heterogeneous treatment effects using machine learning methods, especially for healthcare ...
Machine Learning Estimation of Heterogeneous Treatment Effects ...
heterogeneous effect model, but also the projections of the true model in simpler hypothesis spaces for interpretability. Moreover, our work leverages ...
Metalearners for estimating heterogeneous treatment effects using ...
We describe a number of metaalgorithms that can take advantage of any supervised learning or regression method in machine learning and statistics to estimate ...