走进因果推断

因果推断

1. Introduction to Causal Inference
2. 因果推断学习2 --- 相关性!=因果性 https://zhuanlan.zhihu.com/p/347703807
3. Theoretical Impediments to Machine Learning With Seven Sparks from the Causal Revolution https://arxiv.org/pdf/1801.04016.pdf
4. 因果推断综述及基础方法介绍（一） https://zhuanlan.zhihu.com/p/258562953
5. 因果推理综述——《A Survey on Causal Inference》一文的总结和梳理 因果推理综述——《A Survey on Causal Inference》一文的总结和梳理
6. 因果推断（一）：因果推断两大框架及因果效应 https://zhuanlan.zhihu.com/p/652174282
7. 因果推断笔记（三）上—— 相关理论：Rubin Potential、Pearl https://zhuanlan.zhihu.com/p/559743601
8. 因果科学-Casual-Science https://wqw547243068.github.io/2020/06/30/casual-science/
9. 基于潜在结果框架的因果推断入门 https://zhuanlan.zhihu.com/p/372399985
10. 因果推断笔记（五）——自整理因果推断应用 https://zhuanlan.zhihu.com/p/561152575
11. A Survey of Learning Causality with Data: Problems and Methods https://arxiv.org/pdf/1809.09337.pdf
12. 【综述长文】因果关系是什么？结构因果模型入门 https://zhuanlan.zhihu.com/p/33860572
13. 因果推断 - 干预 因果推断与干预效应-优快云博客
14. 灵魂三问：因果推断 灵魂三问：因果推断
15. causal discovery的算法 https://zhuanlan.zhihu.com/p/627805655
16. 大白话谈因果系列文章（一）：因果推断简介及论文介绍 https://zhuanlan.zhihu.com/p/397796913
17. 因果推断学习笔记（五）：画画因果图 因果推断学习笔记（五）：画画因果图 | Yishi Lin
18. 【因果推断】一文读懂潜在结果框架(Rubin因果模型）的三个假设 https://zhuanlan.zhihu.com/p/484963104
19. 因果推断中的Ignorability假设 https://zhuanlan.zhihu.com/p/356635697?utm_psn=1689684308170891264
20. 因果推断中的可忽略性假设怎么理解？以及这个公式怎么理解？ https://www.zhihu.com/question/416239477/answer/2261849742?utm_psn=1689684246803886080
21. 快手因果推断与实验设计 https://zhuanlan.zhihu.com/p/399274589
22. A Survey on Causal Inference https://arxiv.org/pdf/2002.02770.pdf
23. 大白话谈因果系列文章（二）因果效应估计及论文介绍 https://zhuanlan.zhihu.com/p/397974913
24. NONPARAMETRIC ESTIMATION OF AVERAGE TREATMENT EFFECTS UNDER EXOGENEITY: A REVIEW* http://www.stat.columbia.edu/~gelman/stuff_for_blog/imbens.pdf
25. Estimation of Regression Coefficients When Some Regressors are not Always Observed https://www.tandfonline.com/doi/abs/10.1080/01621459.1994.10476818
26. Covariate balancing propensity score https://imai.fas.harvard.edu/research/files/CBPS.pdf
27. Covariate balancing propensity score for a continuous treatment: Application to the efficacy of political advertisements https://projecteuclid.org/journals/annals-of-applied-statistics/volume-12/issue-1/Covariate-balancing-propensity-score-for-a-continuous-treatment--Application/10.1214/17-AOAS1101.full
28. Treatment Effect Estimation with Data-Driven Variable Decomposition Treatment Effect Estimation with Data-Driven Variable Decomposition| Proceedings of the AAAI Conference on Artificial Intelligence
29. Matching Methods for Causal Inference: A Review and a Look Forward https://arxiv.org/pdf/1010.5586.pdf
30. The Prognostic Analogue of the Propensity Score https://web.archive.org/web/20170811115744id_/http://www.nyu.edu/gsas/dept/politics/seminars/analogue2007-03.pdf
31. Informative Subspace Learning for Counterfactual Inference Informative Subspace Learning for Counterfactual Inference| Proceedings of the AAAI Conference on Artificial Intelligence
32. Metalearners for estimating heterogeneous treatmenteffects using machine learning https://www.pnas.org/doi/epdf/10.1073/pnas.1804597116
33. Quasi-Oracle Estimation of Heterogeneous Treatment Effects https://arxiv.org/pdf/1712.04912.pdf
34. 断点回归（RDD） https://zhuanlan.zhihu.com/p/34477399
35. 怎么用通俗的语言解释断点回归？它与DID的区别是什么 https://www.zhihu.com/question/39613256
36. Estimation and Inference of Heterogeneous Treatment Effects using Random Forests https://arxiv.org/pdf/1510.04342.pdf
37. 因果森林总结：基于树模型的异质因果效应估计 https://zhuanlan.zhihu.com/p/448524822
38. 使用随机森林进行因果推断 https://zhuanlan.zhihu.com/p/46803675
39. BART简介（Bayesian Additive Regression Trees） https://zhuanlan.zhihu.com/p/444501704
40. Deep Counterfactual Networks with Propensity-Dropout https://arxiv.org/pdf/1706.05966.pdf
41. 大白话谈因果系列文章（四）估计uplift--深度学习方法 https://zhuanlan.zhihu.com/p/398938743
42. Learning Representations for Counterfactual Inference https://arxiv.org/pdf/1605.03661.pdf
43. 因果推断系列三（Representation Balance） https://zhuanlan.zhihu.com/p/599900230
44. Estimating individual treatment effect: generalization bounds and algorithms https://arxiv.org/pdf/1606.03976.pdf
45. 因果推断笔记 | 因果推断中的表示学习 TarNet & CFRNet https://zhuanlan.zhihu.com/p/603499723
46. Representation Learning for Treatment Effect Estimation from Observational Data Representation Learning for Treatment Effect Estimation from Observational Data
47. Causal Effect Inference with Deep Latent-Variable Models https://arxiv.org/pdf/1705.08821.pdf
48. 机器学习方法—优雅的模型（一）：变分自编码器（VAE） https://zhuanlan.zhihu.com/p/348498294
49. Learning Representations for Counterfactual Inference https://proceedings.mlr.press/v67/gutierrez17a/gutierrez17a.pdf
50. A Large Scale Benchmark for Uplift Modeling http://ama.imag.fr/~amini/Publis/large-scale-benchmark.pdf
51. 【Uplift】评估方法篇 https://zhuanlan.zhihu.com/p/363082639
52. https://zhuanlan.zhihu.com/p/343747851 https://zhuanlan.zhihu.com/p/343747851
53. uplift模型评估指标及分析 https://zhuanlan.zhihu.com/p/493811028
54. 闲聊因果效应（4）：离线评估 https://zhuanlan.zhihu.com/p/627342229
55. https://baijiahao.baidu.com/s?id=1632749462807280661 百度安全验证
56. Uplift⼴告增效衡量⽅案 https://qzonestyle.gtimg.cn/open_proj/gdt_gw/cms/uploads/Uplift20190524.pdf
57. 因果推断笔记——数据科学领域因果推断案例集锦（九） https://zhuanlan.zhihu.com/p/410055461
58. 腾讯基于因果效应建模的PUSH配额优化实践 腾讯基于因果效应建模的PUSH配额优化实践
59. https://www.woshipm.com/data-analysis/5473759.html 用因果推断解决的四类业务分析难题 | 人人都是产品经理
60. 因果推断实战：淘宝3D化价值分析小结 因果推断实战：淘宝3D化价值分析小结
61. DiDi Food中的智能补贴实战漫谈 DiDi Food中的智能补贴实战漫谈
62. 携程火车票基于因果推断的业务实践 https://www.51cto.com/article/758909.html
63. 因果推断在腾讯游戏中的应用 https://zhuanlan.zhihu.com/p/582767172