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 451–475 of 1722 papers

TitleStatusHype
Causal Inference with Treatment Measurement Error: A Nonparametric Instrumental Variable Approach—0
Unveiling Environmental Sensitivity of Individual Gains in Influence Maximization—0
Causal Information Bottleneck Boosts Adversarial Robustness of Deep Neural Network—0
Rolling with the Punches: Resilient Contrastive Pre-training under Non-Stationary Drift—0
Adversarial Orthogonal Regression: Two non-Linear Regressions for Causal Inference—0
A primer on optimal transport for causal inference with observational data—0
Causal Intervention for Subject-Deconfounded Facial Action Unit Recognition—0
Causal Intervention for Weakly-Supervised Semantic Segmentation—0
Causal Interventions in Bond Multi-Dealer-to-Client Platforms—0
Causal Investigation of Public Opinion during the COVID-19 Pandemic via Social Media Text—0
Causality-Aided Trade-off Analysis for Machine Learning Fairness—0
Causality and Batch Reinforcement Learning: Complementary Approaches To Planning In Unknown Domains—0
Causal Effect Estimation: Recent Advances, Challenges, and Opportunities—0
Causality-Aware Neighborhood Methods for Recommender Systems—0
Causality, Causal Discovery, and Causal Inference in Structural Engineering—0
Causality-Driven Audits of Model Robustness—0
BayesIMP: Uncertainty Quantification for Causal Data Fusion—0
Causality for Earth Science -- A Review on Time-series and Spatiotemporal Causality Methods—0
Analysing the Direction of Emotional Influence in Nonverbal Dyadic Communication: A Facial-Expression Study—0
Causality for Natural Language Processing—0
Causal Q-Aggregation for CATE Model Selection—0
Causality in cardiorespiratory signals in pediatric cardiac patients—0
Causality in cognitive neuroscience: concepts, challenges, and distributional robustness—0
Causality in the Can: Diet Coke's Impact on Fatness—0
A Primer on Causality in Data Science—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