diff --git a/docs/source/index.rst b/docs/source/index.rst index 045445f..91622cb 100644 --- a/docs/source/index.rst +++ b/docs/source/index.rst @@ -9,7 +9,7 @@ CausalEGM - An Encoding Generative Modeling Approach to Dimension Reduction and .. include:: _key_contributors.rst -Causal inference has become extremely essential in modern observational studies with rich covariate information. However, it is often challenging to estimate the causal effect with high-dimensional covariates +Causal inference has become an extremely essential topic in modern observational studies with rich covariate information. However, it is often challenging to estimate the causal effect with high-dimensional covariates due to the “curse of dimensionality”. We develop **CausalEGM**, a deep learning framework for nonlinear dimension reduction and generative modeling of the dependency among covariate features affecting treatment and response.