SOTAVerified

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 601–625 of 1722 papers

TitleStatusHype
Controlling for Unobserved Confounding with Large Language Model Classification of Patient Smoking Status—0
Controlling Learned Effects to Reduce Spurious Correlations in Text Classifiers—0
Causal-Copilot: An Autonomous Causal Analysis Agent—0
Cooperative Causal GraphSAGE—0
Conceptualizing Treatment Leakage in Text-based Causal Inference—0
Correcting invalid regression discontinuity designs with multiple time period data—0
Counterfactual Analysis of the Impact of the IMF Program on Child Poverty in the Global-South Region using Causal-Graphical Normalizing Flows—0
Causal DAG extraction from a library of books or videos/movies—0
CausalAPM: Generalizable Literal Disentanglement for NLU Debiasing—0
Counterfactual-based Root Cause Analysis for Dynamical Systems—0
Customer Price Sensitivities in Competitive Automobile Insurance Markets—0
Computing Functions of Random Variables via Reproducing Kernel Hilbert Space Representations—0
Computer-Assisted Text Analysis for Social Science: Topic Models and Beyond—0
Counterfactual Estimation and Optimization of Click Metrics for Search Engines—0
Counterfactual Evaluation of Treatment Assignment Functions with Networked Observational Data—0
Causal and Counterfactual Views of Missing Data Models—0
Counterfactual Explanation and Causal Inference in Service of Robustness in Robot Control—0
Counterfactual Explanation for Fairness in Recommendation—0
Application of targeted maximum likelihood estimation in public health and epidemiological studies: a systematic review—0
Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder—0
Counterfactual Fairness with Partially Known Causal Graph—0
Computational identification of ketone metabolism as a key regulator of sleep stability and circadian dynamics via real-time metabolic profiling—0
Computational Causal Inference—0
Adaptive Doubly Robust Estimator from Non-stationary Logging Policy under a Convergence of Average Probability—0
Causal and anti-causal learning in pattern recognition for neuroimaging—0
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All datasetsIHDPJobsIDHP

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