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 76100 of 1722 papers

TitleStatusHype
Causal Inference in Recommender Systems: A Survey and Future DirectionsCode1
Causal Modeling of Twitter Activity During COVID-19Code1
Adversarial Counterfactual Learning and Evaluation for Recommender SystemCode1
MiranDa: Mimicking the Learning Processes of Human Doctors to Achieve Causal Inference for Medication RecommendationCode1
A Structural Causal Model for MR Images of Multiple SclerosisCode1
Causal Reinforcement Learning using Observational and Interventional DataCode1
Causal Rule Ensemble: Interpretable Discovery and Inference of Heterogeneous Treatment EffectsCode1
A Brief Introduction to Causal Inference in Machine LearningCode1
A Survey of Deep Causal Models and Their Industrial ApplicationsCode1
Causal Inference-Based Root Cause Analysis for Online Service Systems with Intervention RecognitionCode1
A Survey on Causal Inference for RecommendationCode1
Auto IV: Counterfactual Prediction via Automatic Instrumental Variable DecompositionCode1
Automatic Detection of Influential Actors in Disinformation NetworksCode1
A framework for causal segmentation analysis with machine learning in large-scale digital experimentsCode1
COLA: Contextualized Commonsense Causal Reasoning from the Causal Inference PerspectiveCode1
Contextual Debiasing for Visual Recognition With Causal MechanismsCode1
Autoregressive flow-based causal discovery and inferenceCode1
Causal Incremental Graph Convolution for Recommender System RetrainingCode1
Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identificationCode1
A Constraint-Based Algorithm For Causal Discovery with Cycles, Latent Variables and Selection BiasCode1
CausalEGM: a general causal inference framework by encoding generative modelingCode1
A Graph Neural Network Framework for Causal Inference in Brain NetworksCode1
Counterfactual Variable Control for Robust and Interpretable Question AnsweringCode1
Can Large Language Models Infer Causation from Correlation?Code1
Causal Inference for Chatting HandoffCode1
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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