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 1176–1200 of 1722 papers

TitleStatusHype
Causal Modeling with Stochastic Confounders—0
A Causal Perspective on Loan Pricing: Investigating the Impacts of Selection Bias on Identifying Bid-Response Functions—0
Accounting for Missing Covariates in Heterogeneous Treatment Estimation—0
Accurate Use of Label Dependency in Multi-Label Text Classification Through the Lens of Causality—0
Achieving Counterfactual Fairness for Causal Bandit—0
Achieving Reliable Causal Inference with Data-Mined Variables: A Random Forest Approach to the Measurement Error Problem—0
A Compositional Atlas for Algebraic Circuits—0
A continuous Structural Intervention Distance to compare Causal Graphs—0
A Counterfactual Analysis of the Dishonest Casino—0
Acquiring and Generalizing Causal Inference Rules from Deverbal Noun Constructions—0
A Critical Look at the Consistency of Causal Estimation With Deep Latent Variable Models—0
A Critical Review of Causal Reasoning Benchmarks for Large Language Models—0
Action needed to make carbon offsets from tropical forest conservation work for climate change mitigation—0
Active and Passive Causal Inference Learning—0
The Adaptive Doubly Robust Estimator for Policy Evaluation in Adaptive Experiments and a Paradox Concerning Logging Policy—0
Adaptive Multi-Source Causal Inference—0
A Data-Driven Two-Phase Multi-Split Causal Ensemble Model for Time Series—0
ADCB: An Alzheimer's disease benchmark for evaluating observational estimators of causal effects—0
AD-EE: Early Exiting for Fast and Reliable Vision-Language Models in Autonomous Driving—0
A Deep Causal Inference Approach to Measuring the Effects of Forming Group Loans in Online Non-profit Microfinance Platform—0
A deep causal inference model for fully-interpretable travel behaviour analysis—0
A Density Ratio Super Learner—0
A design of human-like robust AI machines in object identification—0
A discriminative approach for finding and characterizing positivity violations using decision trees—0
Adjusting for Confounders with Text: Challenges and an Empirical Evaluation Framework for Causal Inference—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