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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

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Showing 151–200 of 1722 papers

TitleStatusHype
COLA: Contextualized Commonsense Causal Reasoning from the Causal Inference PerspectiveCode1
Collective Privacy Recovery: Data-sharing Coordination via Decentralized Artificial IntelligenceCode1
Contextual Debiasing for Visual Recognition With Causal MechanismsCode1
Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential EquationsCode1
Automatic Detection of Influential Actors in Disinformation NetworksCode1
Can Large Language Models Infer Causation from Correlation?Code1
Adversarial Counterfactual Learning and Evaluation for Recommender SystemCode1
Counterfactual Explainable RecommendationCode1
A Practical Introduction to Bayesian Estimation of Causal Effects: Parametric and Nonparametric ApproachesCode1
MiranDa: Mimicking the Learning Processes of Human Doctors to Achieve Causal Inference for Medication RecommendationCode1
C-XGBoost: A tree boosting model for causal effect estimationCode1
DagSim: Combining DAG-based model structure with unconstrained data types and relations for flexible, transparent, and modularized data simulationCode1
Deep Counterfactual Estimation with Categorical Background VariablesCode1
Auto IV: Counterfactual Prediction via Automatic Instrumental Variable DecompositionCode1
DiffPO: A causal diffusion model for learning distributions of potential outcomesCode1
Disentangling ID and Modality Effects for Session-based RecommendationCode1
CA-SpaceNet: Counterfactual Analysis for 6D Pose Estimation in SpaceCode1
Double Machine Learning for Static Panel Models with Fixed EffectsCode1
Causal Counterfactuals for Improving the Robustness of Reinforcement LearningCode1
Causal Incremental Graph Convolution for Recommender System RetrainingCode1
Eliciting Causal Abilities in Large Language Models for Reasoning TasksCode1
Empirical Analysis of Model Selection for Heterogeneous Causal Effect EstimationCode1
Estimating Causal Effects Under Image Confounding Bias with an Application to Poverty in AfricaCode1
Estimating individual treatment effect: generalization bounds and algorithmsCode1
Exploring Multi-Modal Data with Tool-Augmented LLM Agents for Precise Causal DiscoveryCode1
FedECA: A Federated External Control Arm Method for Causal Inference with Time-To-Event Data in Distributed SettingsCode1
A Structural Causal Model for MR Images of Multiple SclerosisCode1
Causality-Inspired Fair Representation Learning for Multimodal RecommendationCode1
A Survey of Deep Causal Models and Their Industrial ApplicationsCode1
A framework for causal segmentation analysis with machine learning in large-scale digital experimentsCode1
Causal Modeling with Stationary DiffusionsCode1
Graph Out-of-Distribution Generalization via Causal InterventionCode1
Instrumental Variable Identification of Dynamic Variance DecompositionsCode1
A Survey on Causal Inference for RecommendationCode1
Integrating Earth Observation Data into Causal Inference: Challenges and OpportunitiesCode1
Invariant Anomaly Detection under Distribution Shifts: A Causal PerspectiveCode1
Counterfactual VQA: A Cause-Effect Look at Language BiasCode1
Invariant Representation Learning for Treatment Effect EstimationCode1
Language Models as Causal Effect GeneratorsCode1
Language Models Represent Beliefs of Self and OthersCode1
Learning Invariant Representations for Reinforcement Learning without ReconstructionCode1
An End-to-End Framework to Identify Pathogenic Social Media Accounts on Twitter—0
An End-to-End Framework for Marketing Effectiveness Optimization under Budget Constraint—0
ADCB: An Alzheimer's disease benchmark for evaluating observational estimators of causal effects—0
An Empirical Comparison of Weak-IV-Robust Procedures in Just-Identified Models—0
An Efficient Doubly-Robust Test for the Kernel Treatment Effect—0
A Data-Driven Two-Phase Multi-Split Causal Ensemble Model for Time Series—0
A Causal Inference Framework for Data Rich Environments—0
A causal inference approach of monosynapses from spike trains—0
Ancestral Instrument Method for Causal Inference without Complete Knowledge—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