JeanKaddour/SIN
Causal Effect Inference for Structured Treatments (SIN) (NeurIPS 2021)
This project helps researchers understand how different 'treatments'—like specific drug molecules or network structures—impact an outcome, especially when those treatments are complex. You provide data on structured treatments and their corresponding outcomes, and the system estimates the precise effect of each treatment. It's designed for scientists or analysts studying cause-and-effect relationships with complex, structured data.
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Use this if you need to determine the causal effect of structured inputs, such as chemical compounds or social network configurations, on a specific outcome.
Not ideal if your treatments are simple, unstructured categories or continuous values, or if you're not interested in isolating causal effects.
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Language
Python
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Last pushed
Apr 26, 2022
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