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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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 851–875 of 1722 papers

TitleStatusHype
Semidefinite tests for latent causal structures—0
Semiparametric Triple Difference Estimators—0
The Decaying Missing-at-Random Framework: Model Doubly Robust Causal Inference with Partially Labeled Data—0
Sensitivity Maps of the Hilbert-Schmidt Independence Criterion—0
Shared Causal Paths underlying Alzheimer's dementia and Type 2 Diabetes—0
Short-term shock, long-lasting payment: Evidence from the Lushan Earthquake—0
Signal Processing on Directed Graphs—0
Simple rules for complex decisions—0
Simplifying Causality: A Brief Review of Philosophical Views and Definitions with Examples from Economics, Education, Medicine, Policy, Physics and Engineering—0
Simplifying Probabilistic Expressions in Causal Inference—0
Size of Interventional Markov Equivalence Classes in Random DAG Models—0
Slangvolution: A Causal Analysis of Semantic Change and Frequency Dynamics in Slang—0
Smaller Confidence Intervals From IPW Estimators via Data-Dependent Coarsening—0
Smiles in Profiles: Improving Efficiency While Reducing Disparities in Online Marketplaces—0
Some Reflections on Drawing Causal Inference using Textual Data: Parallels Between Human Subjects and Organized Texts—0
Sparse Nested Markov models with Log-linear Parameters—0
Spectral Representation Learning for Conditional Moment Models—0
Spillover Detection for Donor Selection in Synthetic Control Models—0
Split-Treatment Analysis to Rank Heterogeneous Causal Effects for Prospective Interventions—0
SPORTSCausal: Spill-Over Time Series Causal Inference—0
Stability of Linear Structural Equation Models of Causal Inference—0
Stabilized Inverse Probability Weighting via Isotonic Calibration—0
Stable and Causal Inference for Discriminative Self-supervised Deep Visual Representations—0
Statistical Agnostic Regression: a machine learning method to validate regression models—0
STGCN-LSTM for Olympic Medal Prediction: Dynamic Power Modeling and Causal Policy Optimization—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Random ForestAverage Treatment Effect Error0.96—Unverified
2Balancing Linear RegressionAverage Treatment Effect Error0.93—Unverified
3k-NNAverage Treatment Effect Error0.79—Unverified
4CEVAEAverage Treatment Effect Error0.46—Unverified
5Balancing Neural NetworkAverage Treatment Effect Error0.42—Unverified
6Causal ForestAverage Treatment Effect Error0.4—Unverified
7BCAUS DRAverage Treatment Effect Error0.29—Unverified
8TARNetAverage Treatment Effect Error0.28—Unverified
9Counterfactual Regression + WASSAverage Treatment Effect Error0.27—Unverified
10MTDL-KNNAverage Treatment Effect Error0.23—Unverified
#ModelMetricClaimedVerifiedStatus
1CFR WASSAverage Treatment Effect on the Treated Error0.09—Unverified
2CFR MMDAverage Treatment Effect on the Treated Error0.08—Unverified
3BARTAverage Treatment Effect on the Treated Error0.08—Unverified
4GANITEAverage Treatment Effect on the Treated Error0.06—Unverified
5BCAUSSAverage Treatment Effect on the Treated Error0.05—Unverified
#ModelMetricClaimedVerifiedStatus
1BARTAverage Treatment Effect Error0.34—Unverified
2OLS with separate regressors for each treatmentAverage Treatment Effect Error0.31—Unverified
3Average Treatment Effect Error-0.23—Unverified