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 301–350 of 1722 papers

TitleStatusHype
See or Guess: Counterfactually Regularized Image CaptioningCode1
Causal Rule Forest: Toward Interpretable and Precise Treatment Effect Estimation—0
Using LLMs for Explaining Sets of Counterfactual Examples to Final UsersCode0
Can Transformers Do Enumerative Geometry?Code0
General targeted machine learning for modern causal mediation analysisCode1
DynamicRouteGPT: A Real-Time Multi-Vehicle Dynamic Navigation Framework Based on Large Language Models—0
Measuring Variable Importance in Heterogeneous Treatment Effects with ConfidenceCode0
Multi-Treatment Multi-Task Uplift Modeling for Enhancing User Growth—0
Towards Deconfounded Image-Text Matching with Causal Inference—0
SPORTSCausal: Spill-Over Time Series Causal Inference—0
End-to-End Cost-Effective Incentive Recommendation under Budget Constraint with Uplift Modeling—0
Counterfactual and Synthetic Control Method: Causal Inference with Instrumented Principal Component AnalysisCode0
Multi-task Heterogeneous Graph Learning on Electronic Health RecordsCode1
χSPN: Characteristic Interventional Sum-Product Networks for Causal Inference in Hybrid DomainsCode0
Causal Graph Aided Causal Discovery in an Observational Aneurysmal Subarachnoid Hemorrhage Study—0
Correcting invalid regression discontinuity designs with multiple time period data—0
Generalized Encouragement-Based Instrumental Variables for Counterfactual RegressionCode0
Dynamical causality under invisible confounders—0
A Density Ratio Super Learner—0
Peer-induced Fairness: A Causal Approach for Algorithmic Fairness AuditingCode0
A Multi-class Ride-hailing Service Subsidy System Utilizing Deep Causal Networks—0
DNA-SE: Towards Deep Neural-Nets Assisted Semiparametric EstimationCode0
Identification and Inference for Synthetic Control Methods with Spillover Effects: Estimating the Economic Cost of the Sudan Split—0
MoMa: Efficient Early-Fusion Pre-training with Mixture of Modality-Aware Experts—0
Potential weights and implicit causal designs in linear regression—0
Domain Adaptable Prescriptive AI Agent for Enterprise—0
Large Language Models as Co-Pilots for Causal Inference in Medical Studies—0
Causal modelling without introducing counterfactuals or abstract distributions—0
Establishing Causal Relationship Between Whole Slide Image Predictions and Diagnostic Evidence Subregions in Deep Learning—0
MiranDa: Mimicking the Learning Processes of Human Doctors to Achieve Causal Inference for Medication RecommendationCode1
Causal Inference with Complex Treatments: A Survey—0
Topological Analysis of Seizure-Induced Changes in Brain Hierarchy Through Effective Connectivity—0
Discriminative and Consistent Representation DistillationCode1
Identification of Average Causal Effects in Confounded Additive Noise Models—0
Graph Neural Network Causal Explanation via Neural Causal ModelsCode0
An Introduction to Causal Discovery—0
Causal inference through multi-stage learning and doubly robust deep neural networks—0
Advancements in Recommender Systems: A Comprehensive Analysis Based on Data, Algorithms, and Evaluation—0
A Critical Review of Causal Reasoning Benchmarks for Large Language Models—0
Identifying Macro Conditional Independencies and Macro Total Effects in Summary Causal Graphs with Latent Confounding—0
New User Event Prediction Through the Lens of Causal Inference—0
Towards Context-Aware Emotion Recognition Debiasing from a Causal Demystification Perspective via De-confounded Training—0
Representation learning with CGAN for casual inference—0
CURLS: Causal Rule Learning for Subgroups with Significant Treatment Effect—0
Minimum Reduced-Order Models via Causal Inference—0
The Computational Curse of Big Data for Bayesian Additive Regression Trees: A Hitting Time AnalysisCode0
Credit Ratings: Heterogeneous Effect on Capital Structure—0
Compositional Models for Estimating Causal Effects—0
Causal Inference with Latent Variables: Recent Advances and Future Prospectives—0
Integrating Fuzzy Logic with Causal Inference: Enhancing the Pearl and Neyman-Rubin Methodologies—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