Research map / Probabilistic and scientific modeling / Treatment effects
Imbalance-Aware Uplift Modeling for Observational Data
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use IAUM instead of SDRM | uplift modeling · Industrial dataset | Qini coefficient: 0.468 -> 0.593 | Helped |
| Use IAUM instead of TDVAE | uplift modeling · imbalanced RHC dataset | Qini coefficient: 0.0130 -> 0.0143 | Helped |
| Use IAUM instead of TOM | uplift modeling · imbalanced RHC dataset | Qini coefficient: 0.0078 -> 0.0143 | Helped |
| Increase treatment-group share from 0.1 toward 0.5 | IAUM and baseline uplift estimators · Synthetic scenario 8 | bias | Mixed |
| Compare treatment-outcome and control-outcome prediction under imbalance | potential-outcome models · Synthetic dataset | MAE | Mixed |
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- Assessing the robustness of heterogeneous treatment effects in survival analysis under informative censoring (NeurIPS 2026 · similarity 0.84)
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