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

Showing 526550 of 1722 papers

TitleStatusHype
Calibration Strategies for Robust Causal Estimation: Theoretical and Empirical Insights on Propensity Score-Based EstimatorsCode0
Causal Walk: Debiasing Multi-Hop Fact Verification with Front-Door AdjustmentCode0
An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic ControlsCode0
Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference ModelsCode0
Bridging Nations: Quantifying the Role of Multilinguals in Communication on Social MediaCode0
A Causal Inference Method for Reducing Gender Bias in Word Embedding RelationsCode0
Counterfactually Comparing Abstaining ClassifiersCode0
Convolutional neural networks for valid and efficient causal inferenceCode0
Counterfactual FairnessCode0
Estimation of Causal Effects in the Presence of Unobserved Confounding in the Alzheimer's ContinuumCode0
CORECODE: A Common Sense Annotated Dialogue Dataset with Benchmark Tasks for Chinese Large Language ModelsCode0
Causal-StoNet: Causal Inference for High-Dimensional Complex DataCode0
Brain-Inspired Visual Odometry: Balancing Speed and Interpretability through a System of Systems ApproachCode0
Counterfactual and Synthetic Control Method: Causal Inference with Instrumented Principal Component AnalysisCode0
CGNSDE: Conditional Gaussian Neural Stochastic Differential Equation for Modeling Complex Systems and Data AssimilationCode0
CausalSR: Structural Causal Model-Driven Super-Resolution with Counterfactual InferenceCode0
Causal Estimation of Exposure Shifts with Neural NetworksCode0
Confounding Feature Acquisition for Causal Effect EstimationCode0
Consistent Estimation of Propensity Score Functions with Oversampled Exposed SubjectsCode0
Compositional Probabilistic and Causal Inference using Tractable Circuit ModelsCode0
Comparison between instrumental variable and mediation-based methods for reconstructing causal gene networks in yeastCode0
Can We Validate Counterfactual Estimations in the Presence of General Network Interference?Code0
Debiased Bayesian inference for average treatment effectsCode0
A neural network oracle for quantum nonlocality problems in networksCode0
Combinatorial Causal BanditsCode0
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Benchmark Results

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