Corpus ID: 211066551

A Survey on Causal Inference

@article{Yao2020ASO,
  title={A Survey on Causal Inference},
  author={Liuyi Yao and Zhixuan Chu and Sheng Li and Y. Li and Jing Gao and A. Zhang},
  journal={ArXiv},
  year={2020},
  volume={abs/2002.02770}
}
Causal inference is a critical research topic across many domains, such as statistics, computer science, education, public policy and economics, for decades. Nowadays, estimating causal effect from observational data has become an appealing research direction owing to the large amount of available data and low budget requirement, compared with randomized controlled trials. Embraced with the rapidly developed machine learning area, various causal effect estimation methods for observational data… Expand
11 Citations
CONTINUAL LIFELONG CAUSAL EFFECT INFERENCE
  • 2020
  • Highly Influenced
Causal inference methods for combining randomized trials and observational studies: a review
  • 4
  • PDF
Targeted VAE: Structured Inference and Targeted Learning for Causal Parameter Estimation
  • 4
  • PDF
Learning Decomposed Representation for Counterfactual Inference
  • 1
  • PDF
Clinically Relevant Mediation Analysis using Controlled Indirect Effect
  • Highly Influenced
  • PDF
Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models
  • PDF
Poincare: Recommending Publication Venues via Treatment Effect Estimation
  • PDF
...
1
2
...

References

SHOWING 1-10 OF 171 REFERENCES
Identification and Estimation of Causal Effects from Dependent Data
  • 11
  • PDF
Benchmarking Framework for Performance-Evaluation of Causal Inference Analysis
  • 17
  • PDF
Estimation and Inference of Heterogeneous Treatment Effects using Random Forests
  • 841
  • PDF
Machine Learning Methods for Estimating Heterogeneous Causal Eects
  • 47
Learning Individual Treatment Effects from Networked Observational Data
  • 6
  • Highly Influential
  • PDF
Matching methods for causal inference: A review and a look forward.
  • E. Stuart
  • Computer Science, Medicine
  • Statistical science : a review journal of the Institute of Mathematical Statistics
  • 2010
  • 2,647
  • PDF
Estimating individual treatment effect: generalization bounds and algorithms
  • 291
  • Highly Influential
  • PDF
Causal inference in statistics: An overview
  • 1,062
  • PDF
...
1
2
3
4
5
...