Causal Machine Learning: A Survey and Open Problems(因果机器学习：调查与未解决的问题)

论文地址：[2206.15475] Causal Machine Learning: A Survey and Open Problems (arxiv.org)

1.该篇论文主要工作：

1).categorize work in CausalML into five groups according to the problems they tackle:(1) causal supervised learning,(2) causal generative modeling,(3) causal explanations,(4) causal fairness,(5) causal reinforcement learning.

2).systematically compare its methods and point out open problems。

3).provide an overview of causal benchmarks and a critical discussion of the state of this nascent field, including recommendations for future work.

 

 

2.重点内容：

1).Causal Supervised Learning

 

2).Causal Generative Modeling

 

3).Causal Explanations

 

4).Causal Fairness

 

5).Causal Reinforcement Learning

 

6).Modality-specific Applications

7).Causal Benchmarks