Preventing Spurious Interactions: A New Inductive Bias for Accurate Treatment Effect Estimation
In recent years, the use of non-linear machine learning techniques to estimate treatment effects from observational data has gained significant attention. Many of the most effective methods incorporate specific algorithmic inductive biases that encode causal information, thereby enhancing the precis...
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| Main Authors: | Roger Pros, Jordi Vitria |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11016676/ |
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