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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 51–100 of 1722 papers

TitleStatusHype
Counterfactual Variable Control for Robust and Interpretable Question AnsweringCode1
Counterfactual VQA: A Cause-Effect Look at Language BiasCode1
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
ROCK: Causal Inference Principles for Reasoning about Commonsense CausalityCode1
Active Bayesian Causal InferenceCode1
DiffPO: A causal diffusion model for learning distributions of potential outcomesCode1
Disentangling ID and Modality Effects for Session-based RecommendationCode1
Causality for Tabular Data Synthesis: A High-Order Structure Causal Benchmark FrameworkCode1
Double Machine Learning for Static Panel Models with Fixed EffectsCode1
Causal Parrots: Large Language Models May Talk Causality But Are Not CausalCode1
Collective Privacy Recovery: Data-sharing Coordination via Decentralized Artificial IntelligenceCode1
Causal Inference for Chatting HandoffCode1
Causal Incremental Graph Convolution for Recommender System RetrainingCode1
Causal Inference for Qualitative OutcomesCode1
Causal Effect Inference with Deep Latent-Variable ModelsCode1
CausalBench: A Large-scale Benchmark for Network Inference from Single-cell Perturbation DataCode1
Causal Counterfactuals for Improving the Robustness of Reinforcement LearningCode1
causalgraph: A Python Package for Modeling, Persisting and Visualizing Causal Graphs Embedded in Knowledge GraphsCode1
Causal Inference for Spatial TreatmentsCode1
Autoregressive flow-based causal discovery and inferenceCode1
CausalCite: A Causal Formulation of Paper CitationsCode1
Can Large Language Models Infer Causation from Correlation?Code1
CausalEGM: a general causal inference framework by encoding generative modelingCode1
Causal Image Modeling for Efficient Visual UnderstandingCode1
CausalImages: An R Package for Causal Inference with Earth Observation, Bio-medical, and Social Science ImagesCode1
Causal Inference-Based Root Cause Analysis for Online Service Systems with Intervention RecognitionCode1
Adversarial Counterfactual Learning and Evaluation for Recommender SystemCode1
MiranDa: Mimicking the Learning Processes of Human Doctors to Achieve Causal Inference for Medication RecommendationCode1
Causal Inference in Recommender Systems: A Survey of Strategies for Bias Mitigation, Explanation, and GeneralizationCode1
Training a Resilient Q-Network against Observational InterferenceCode1
Causal Inference with the Instrumental Variable Approach and Bayesian Nonparametric Machine LearningCode1
Auto IV: Counterfactual Prediction via Automatic Instrumental Variable DecompositionCode1
Causal Knowledge Guided Societal Event ForecastingCode1
CausalMob: Causal Human Mobility Prediction with LLMs-derived Human Intentions toward Public EventsCode1
Causal Modeling of Twitter Activity During COVID-19Code1
Causal Proxy Models for Concept-Based Model ExplanationsCode1
Causal Recurrent Variational Autoencoder for Medical Time Series GenerationCode1
A framework for causal segmentation analysis with machine learning in large-scale digital experimentsCode1
Causal Rule Ensemble: Interpretable Discovery and Inference of Heterogeneous Treatment EffectsCode1
Causal Unsupervised Semantic SegmentationCode1
A Survey on Causal Inference for RecommendationCode1
Automatic Detection of Influential Actors in Disinformation NetworksCode1
CEBaB: Estimating the Causal Effects of Real-World Concepts on NLP Model BehaviorCode1
A Constraint-Based Algorithm For Causal Discovery with Cycles, Latent Variables and Selection BiasCode1
Contextual Debiasing for Visual Recognition With Causal MechanismsCode1
A Graph Neural Network Framework for Causal Inference in Brain NetworksCode1
Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identificationCode1
Counterfactual Explainable RecommendationCode1
CA-SpaceNet: Counterfactual Analysis for 6D Pose Estimation in SpaceCode1
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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