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What is Causal Inference with Latent Variables about?
Kosuke Imai discusses causal inference with latent variables, focusing on the implications of structural latent factor models and their application in identifying causal relationships. The document highlights key results, including a statistical test for structural interpretations and questions regarding the identifiability of factor models. Additionally, it references follow-up work by Wang and Blei on deconfounder methodology using factor models to address unobserved multi-cause confounders.
- Author
- g4briel.santanna
- Language
- EN