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 125 of 1722 papers

TitleStatusHype
Estimating Interventional Distributions with Uncertain Causal Graphs through Meta-Learning0
Quantum Neural Networks for Propensity Score Estimation and Survival Analysis in Observational Biomedical Studies0
Causal-Aware Intelligent QoE Optimization for VR Interaction with Adaptive Keyframe Extraction0
T-CPDL: A Temporal Causal Probabilistic Description Logic for Developing Logic-RAG Agent0
Bayesian Evolutionary Swarm Architecture: A Formal Epistemic System Grounded in Truth-Based Competition0
Causal Interventions in Bond Multi-Dealer-to-Client Platforms0
An Empirical Comparison of Weak-IV-Robust Procedures in Just-Identified Models0
International Trade and Intellectual Property0
From Prompts to Constructs: A Dual-Validity Framework for LLM Research in Psychology0
Learning Causally Predictable Outcomes from Psychiatric Longitudinal DataCode0
Linear-Time Primitives for Algorithm Development in Graphical Causal Inference0
Double Machine Learning for Conditional Moment Restrictions: IV Regression, Proximal Causal Learning and Beyond0
Honesty in Causal Forests: When It Helps and When It Hurts0
Estimation of Treatment Effects in Extreme and Unobserved Data0
Rethinking Distributional IVs: KAN-Powered D-IV-LATE & Model Choice0
Leveraging MIMIC Datasets for Better Digital Health: A Review on Open Problems, Progress Highlights, and Future Promises0
Directed Acyclic Graph Convolutional Networks0
Foundation Models for Causal Inference via Prior-Data Fitted Networks0
From Images to Insights: Explainable Biodiversity Monitoring with Plain Language Habitat ExplanationsCode0
Towards Robust Multimodal Emotion Recognition under Missing Modalities and Distribution ShiftsCode1
Correlation vs causation in Alzheimer's disease: an interpretability-driven study0
STOAT: Spatial-Temporal Probabilistic Causal Inference Network0
Revolutionizing Clinical Trials: A Manifesto for AI-Driven Transformation0
Paths to Causality: Finding Informative Subgraphs Within Knowledge Graphs for Knowledge-Based Causal DiscoveryCode0
Half-AVAE: Adversarial-Enhanced Factorized and Structured Encoder-Free VAE for Underdetermined Independent Component Analysis0
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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