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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 151–200 of 1722 papers

TitleStatusHype
CausalEGM: a general causal inference framework by encoding generative modelingCode1
Causal Effect Inference with Deep Latent-Variable ModelsCode1
General targeted machine learning for modern causal mediation analysisCode1
Auto IV: Counterfactual Prediction via Automatic Instrumental Variable DecompositionCode1
Causal Reinforcement Learning using Observational and Interventional DataCode1
DagSim: Combining DAG-based model structure with unconstrained data types and relations for flexible, transparent, and modularized data simulationCode1
Adversarial Counterfactual Learning and Evaluation for Recommender SystemCode1
Inference and Denoise: Causal Inference-based Neural Speech EnhancementCode1
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
Causal Incremental Graph Convolution for Recommender System RetrainingCode1
Causal Recurrent Variational Autoencoder for Medical Time Series GenerationCode1
Causal Inference for Chatting HandoffCode1
Causal Inference-Based Root Cause Analysis for Online Service Systems with Intervention RecognitionCode1
Language Agents Meet Causality -- Bridging LLMs and Causal World ModelsCode1
Language Models as Causal Effect GeneratorsCode1
CA-SpaceNet: Counterfactual Analysis for 6D Pose Estimation in SpaceCode1
Causal Inference in Recommender Systems: A Survey and Future DirectionsCode1
Learning end-to-end patient representations through self-supervised covariate balancing for causal treatment effect estimationCode1
Learning Individually Inferred Communication for Multi-Agent CooperationCode1
Causal Inference in Recommender Systems: A Survey of Strategies for Bias Mitigation, Explanation, and GeneralizationCode1
Long-Tailed Classification by Keeping the Good and Removing the Bad Momentum Causal EffectCode1
Training a Resilient Q-Network against Observational InterferenceCode1
ROCK: Causal Inference Principles for Reasoning about Commonsense CausalityCode1
Automatic Detection of Influential Actors in Disinformation NetworksCode1
CausalImages: An R Package for Causal Inference with Earth Observation, Bio-medical, and Social Science ImagesCode1
A Structural Causal Model for MR Images of Multiple SclerosisCode1
Causal intersectionality for fair rankingCode1
A Survey of Deep Causal Models and Their Industrial ApplicationsCode1
A framework for causal segmentation analysis with machine learning in large-scale digital experimentsCode1
On Root Cause Localization and Anomaly Mitigation through Causal InferenceCode1
Causality for Tabular Data Synthesis: A High-Order Structure Causal Benchmark FrameworkCode1
dame-flame: A Python Library Providing Fast Interpretable Matching for Causal InferenceCode1
A Survey on Causal Inference for RecommendationCode1
CausalMob: Causal Human Mobility Prediction with LLMs-derived Human Intentions toward Public EventsCode1
Disentangling ID and Modality Effects for Session-based RecommendationCode1
Estimating individual treatment effect: generalization bounds and algorithmsCode1
Causal Modeling with Stationary DiffusionsCode1
Causal Parrots: Large Language Models May Talk Causality But Are Not CausalCode1
A Scoping Review of Earth Observation and Machine Learning for Causal Inference: Implications for the Geography of PovertyCode1
Invariant Causal Prediction for Block MDPsCode1
Counterfactual Reasoning for Multi-Label Image Classification via Patching-Based TrainingCode0
Counterfactual Mean EmbeddingsCode0
Counterfactually Comparing Abstaining ClassifiersCode0
Counterfactual Prediction Under Selective ConfoundingCode0
An Efficient Approach for Optimizing the Cost-effective Individualized Treatment Rule Using Conditional Random ForestCode0
Adaptive Nonparametric Perturbations of Parametric Bayesian ModelsCode0
Ancestral Causal InferenceCode0
A Multi-level Neural Network for Implicit Causality Detection in Web TextsCode0
Counterfactual FairnessCode0
Show:102550
← PrevPage 4 of 35Next →
All datasetsIHDPJobsIDHP

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