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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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 576–600 of 1722 papers

TitleStatusHype
CausalMed: Causality-Based Personalized Medication Recommendation Centered on Patient health stateCode0
Causal Inference for Genomic Data with Multiple Heterogeneous Outcomes—0
CGNSDE: Conditional Gaussian Neural Stochastic Differential Equation for Modeling Complex Systems and Data AssimilationCode0
Counterfactual Reasoning for Multi-Label Image Classification via Patching-Based TrainingCode0
Evaluating Interventional Reasoning Capabilities of Large Language Models—0
Context-dependent Causality (the Non-Nonotonic Case)—0
CAVIAR: Categorical-Variable Embeddings for Accurate and Robust Inference—0
Causality for Earth Science -- A Review on Time-series and Spatiotemporal Causality Methods—0
Propensity Score Alignment of Unpaired Multimodal DataCode0
Predictive Performance Comparison of Decision Policies Under ConfoundingCode0
Unveiling the Impact of Macroeconomic Policies: A Double Machine Learning Approach to Analyzing Interest Rate Effects on Financial Markets—0
Causal Inference for Human-Language Model CollaborationCode0
On Causal Inference with Model-Based OutcomesCode0
De-confounded Data-free Knowledge Distillation for Handling Distribution Shifts—0
Causal-StoNet: Causal Inference for High-Dimensional Complex DataCode0
Can Large Language Models (or Humans) Disentangle Text?Code0
Double Cross-fit Doubly Robust Estimators: Beyond Series RegressionCode0
A Transfer Learning Causal Approach to Evaluate Racial/Ethnic and Geographic Variation in Outcomes Following Congenital Heart Surgery—0
COBRA-PPM: A Causal Bayesian Reasoning Architecture Using Probabilistic Programming for Robot Manipulation Under Uncertainty—0
Research on Personal Credit Risk Assessment Methods Based on Causal Inference—0
Lifted Causal Inference in Relational DomainsCode0
Limits of Approximating the Median Treatment Effect—0
Algorithmic syntactic causal identification—0
Large Language Models and Causal Inference in Collaboration: A Comprehensive Survey—0
Probabilistic Easy Variational Causal Effect—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