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 12011225 of 1722 papers

TitleStatusHype
Weak Instrumental Variables: Limitations of Traditional 2SLS and Exploring Alternative Instrumental Variable Estimators0
Quantum causal inference in the presence of hidden common causes: An entropic approach0
Normalized multivariate time series causality analysis and causal graph reconstruction0
Prospective Artificial Intelligence Approaches for Active Cyber Defence0
Everything Has a Cause: Leveraging Causal Inference in Legal Text AnalysisCode1
Sequential Deconfounding for Causal Inference with Unobserved ConfoundersCode0
Double Robust Semi-Supervised Inference for the Mean: Selection Bias under MAR Labeling with Decaying OverlapCode0
Large-scale nonlinear Granger causality for inferring directed dependence from short multivariate time-series data0
Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals with Application to Proximal Causal InferenceCode0
Multi-Source Causal Inference Using Control Variates0
SUTD-TrafficQA: A Question Answering Benchmark and an Efficient Network for Video Reasoning over Traffic EventsCode1
User-Oriented Smart General AI System under Causal Inference0
Causal Inference Under Unmeasured Confounding With Negative Controls: A Minimax Learning Approach0
Interpretable Machine Learning: Fundamental Principles and 10 Grand Challenges0
SEMgraph: An R Package for Causal Network Analysis of High-Throughput Data with Structural Equation ModelsCode1
Time-uniform central limit theory and asymptotic confidence sequencesCode0
Estimating the causal effect of an intervention in a time series setting: the C-ARIMA approach0
Combining Interventional and Observational Data Using Causal ReductionsCode0
Asymptotic Theory for IV-Based Reinforcement Learning with Potential Endogeneity0
A Structural Causal Model for MR Images of Multiple SclerosisCode1
Oil and Gas Reservoirs Parameters Analysis Using Mixed Learning of Bayesian Networks0
Confronting Machine Learning With Financial Research0
Scalable Causal Domain AdaptationCode0
Online Multi-Armed Bandits with Adaptive Inference0
Case Level Counterfactual Reasoning in Process Mining0
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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