Research map / Probabilistic and scientific modeling / Causal discovery
Fair Inference on Outcomes
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Constrain the NDE to lie between 0.95 and 1.05 | BART on COMPAS · COMPAS test set | accuracy: 67.8 % -> 66.4% | Hurt |
| Remove race from the outcome model (ablation) | BART on COMPAS · COMPAS test set | accuracy: 67.8 % -> 64.0% | Hurt |
| Constrain the PSE to lie between 0.95 and 1.05 | Logistic regression on Adult · Adult test set | accuracy: 82% -> 72% | Hurt |
| Estimate the NDE with a triply robust estimator rather than an estimator relying on the outcome model | Simulation outcome model · Simulation | NDE estimate: 2.7 -> 3.01 | Helped |
| Use constrained coefficients obtained with a misspecified outcome-model-dependent estimator | Simulation outcome model · Simulation | NDE estimate: 2.7 -> 3.07 | Hurt |
Closest papers by meaning
- Fairness-Accuracy Trade-Offs: A Causal Perspective (AAAI 2025 · similarity 0.87)
- Reconciling Predictive and Statistical Parity: A Causal Approach (AAAI 2024 · similarity 0.86)
- Interventional Fairness on Partially Known Causal Graphs: A Constrained Optimization Approach (ICLR 2024 · similarity 0.86)
- Mind the Gap: A Causal Perspective on Bias Amplification in Prediction & Decision-Making (NeurIPS 2024 · similarity 0.86)
- Causal Fairness under Unobserved Confounding: A Neural Sensitivity Framework (ICLR 2024 · similarity 0.86)
- FairPFN: A Tabular Foundation Model for Causal Fairness (ICML 2025 · similarity 0.85)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.