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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 576–600 of 1722 papers

TitleStatusHype
An End-to-End Framework to Identify Pathogenic Social Media Accounts on Twitter—0
Causal programming: inference with structural causal models as finding instances of a relation—0
β-Intact-VAE: Identifying and Estimating Causal Effects under Limited Overlap—0
Causal Probabilistic Spatio-temporal Fusion Transformers in Two-sided Ride-Hailing Markets—0
Biased Stochastic First-Order Methods for Conditional Stochastic Optimization and Applications in Meta Learning—0
An End-to-End Framework for Marketing Effectiveness Optimization under Budget Constraint—0
ADCB: An Alzheimer's disease benchmark for evaluating observational estimators of causal effects—0
Selective machine learning of doubly robust functionals—0
Causal Order Discovery based on Monotonic SCMs—0
An Empirical Comparison of Weak-IV-Robust Procedures in Just-Identified Models—0
Causal nearest neighbor rules for optimal treatment regimes—0
Causal Multi-Level Fairness—0
Local Projections Inference with High-Dimensional Covariates without Sparsity—0
Causal models in string diagrams—0
Causal Models for Growing Networks—0
An Efficient Doubly-Robust Test for the Kernel Treatment Effect—0
A Data-Driven Two-Phase Multi-Split Causal Ensemble Model for Time Series—0
A Causal Inference Framework for Data Rich Environments—0
Causal modelling without introducing counterfactuals or abstract distributions—0
Beyond Patterns: Harnessing Causal Logic for Autonomous Driving Trajectory Prediction—0
Causal Model Analysis using Collider v-structure with Negative Percentage Mapping—0
Beyond Flatland: A Geometric Take on Matching Methods for Treatment Effect Estimation—0
Beyond Correlation: Towards Causal Large Language Model Agents in Biomedicine—0
Causal Mediation Analysis with Hidden Confounders—0
Causal Mediation Analysis Leveraging Multiple Types of Summary Statistics Data—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