Causal Inference
Causal inference is the task of drawing a conclusion about a causal connection based on the conditions of the occurrence of an effect.
( Image credit: Recovery of non-linear cause-effect relationships from linearly mixed neuroimaging data )
Papers
Showing 291–300 of 1722 papers
Benchmark Results
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | Random Forest | Average Treatment Effect Error | 0.96 | — | Unverified |
| 2 | Balancing Linear Regression | Average Treatment Effect Error | 0.93 | — | Unverified |
| 3 | k-NN | Average Treatment Effect Error | 0.79 | — | Unverified |
| 4 | CEVAE | Average Treatment Effect Error | 0.46 | — | Unverified |
| 5 | Balancing Neural Network | Average Treatment Effect Error | 0.42 | — | Unverified |
| 6 | Causal Forest | Average Treatment Effect Error | 0.4 | — | Unverified |
| 7 | BCAUS DR | Average Treatment Effect Error | 0.29 | — | Unverified |
| 8 | TARNet | Average Treatment Effect Error | 0.28 | — | Unverified |
| 9 | Counterfactual Regression + WASS | Average Treatment Effect Error | 0.27 | — | Unverified |
| 10 | MTDL-KNN | Average Treatment Effect Error | 0.23 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | CFR WASS | Average Treatment Effect on the Treated Error | 0.09 | — | Unverified |
| 2 | CFR MMD | Average Treatment Effect on the Treated Error | 0.08 | — | Unverified |
| 3 | BART | Average Treatment Effect on the Treated Error | 0.08 | — | Unverified |
| 4 | GANITE | Average Treatment Effect on the Treated Error | 0.06 | — | Unverified |
| 5 | BCAUSS | Average Treatment Effect on the Treated Error | 0.05 | — | Unverified |
| # | Model | Metric | Claimed | Verified | Status |
|---|---|---|---|---|---|
| 1 | BART | Average Treatment Effect Error | 0.34 | — | Unverified |
| 2 | OLS with separate regressors for each treatment | Average Treatment Effect Error | 0.31 | — | Unverified |
| 3 | Average Treatment Effect Error | -0.23 | — | Unverified |