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 1–10 of 1722 papers

TitleStatusHype
Estimating Interventional Distributions with Uncertain Causal Graphs through Meta-Learning—0
Causal-Aware Intelligent QoE Optimization for VR Interaction with Adaptive Keyframe Extraction—0
Quantum Neural Networks for Propensity Score Estimation and Survival Analysis in Observational Biomedical Studies—0
Bayesian Evolutionary Swarm Architecture: A Formal Epistemic System Grounded in Truth-Based Competition—0
T-CPDL: A Temporal Causal Probabilistic Description Logic for Developing Logic-RAG Agent—0
Causal Interventions in Bond Multi-Dealer-to-Client Platforms—0
An Empirical Comparison of Weak-IV-Robust Procedures in Just-Identified Models—0
International Trade and Intellectual Property—0
From Prompts to Constructs: A Dual-Validity Framework for LLM Research in Psychology—0
Learning Causally Predictable Outcomes from Psychiatric Longitudinal DataCode0
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Benchmark Results

#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