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

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Showing 226–250 of 1722 papers

TitleStatusHype
Estimating Causal Effects in Partially Directed Parametric Causal Factor Graphs—0
Stabilized Inverse Probability Weighting via Isotonic Calibration—0
CRTRE: Causal Rule Generation with Target Trial Emulation Framework—0
CRepair: CVAE-based Automatic Vulnerability Repair Technology—0
Lee Bounds with a Continuous Treatment in Sample Selection—0
A Causal Framework for Precision Rehabilitation—0
Automatic doubly robust inference for linear functionals via calibrated debiased machine learningCode0
Testing Generalizability in Causal Inference—0
Controlling for Unobserved Confounding with Large Language Model Classification of Patient Smoking Status—0
Optimizing Multi-Scale Representations to Detect Effect Heterogeneity Using Earth Observation and Computer Vision: Applications to Two Anti-Poverty RCTs—0
Educational Effects in Mathematics: Conditional Average Treatment Effect depending on the Number of Treatments—0
A Semiparametric Approach to Causal Inference—0
Average Controlled and Average Natural Micro Direct Effects in Summary Causal Graphs—0
Tangent Space Causal Inference: Leveraging Vector Fields for Causal Discovery in Dynamical SystemsCode0
Causality-Driven Audits of Model Robustness—0
An Overview of Causal Inference using Kernel Embeddings—0
Bayesian Counterfactual Prediction Models for HIV Care Retention with Incomplete Outcome and Covariate Information—0
Debiasing Alternative Data for Credit Underwriting Using Causal Inference—0
Estimating Causal Effects of Text Interventions Leveraging LLMs—0
Deep Learning Methods for the Noniterative Conditional Expectation G-Formula for Causal Inference from Complex Observational Data—0
Mechanism learning: Reverse causal inference in the presence of multiple unknown confounding through front-door causal bootstrappingCode0
Language Agents Meet Causality -- Bridging LLMs and Causal World ModelsCode1
Causal Order Discovery based on Monotonic SCMs—0
Cascading Failure Prediction via Causal Inference—0
Deoxys: A Causal Inference Engine for Unhealthy Node Mitigation in Large-scale Cloud Infrastructure—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