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 501–550 of 1722 papers

TitleStatusHype
Identification of Average Causal Effects in Confounded Additive Noise Models—0
Graph Neural Network Causal Explanation via Neural Causal ModelsCode0
Causal inference through multi-stage learning and doubly robust deep neural networks—0
An Introduction to Causal Discovery—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
Advancements in Recommender Systems: A Comprehensive Analysis Based on Data, Algorithms, and Evaluation—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
Probabilistic Temporal Prediction of Continuous Disease Trajectories and Treatment Effects Using Neural SDEs—0
LLMs Are Prone to Fallacies in Causal Inference—0
Standardizing Structural Causal ModelsCode0
Spillover Detection for Donor Selection in Synthetic Control Models—0
Investigating potential causes of Sepsis with Bayesian network structure learning—0
Causal Post-Processing of Predictive Models—0
Counterfactual-based Root Cause Analysis for Dynamical Systems—0
Orthogonalized Estimation of Difference of Q-functions—0
DecoR: Deconfounding Time Series with Robust RegressionCode0
Test-Time Fairness and Robustness in Large Language Models—0
Heterogeneous Treatment Effects in Panel DataCode0
G-Transformer: Counterfactual Outcome Prediction under Dynamic and Time-varying Treatment Regimes—0
Experimental Evaluation of ROS-Causal in Real-World Human-Robot Spatial Interaction Scenarios—0
Reconciling Heterogeneous Effects in Causal Inference—0
Inferring the time-varying coupling of dynamical systems with temporal convolutional autoencodersCode0
A Tutorial on Doubly Robust Learning for Causal Inference—0
Causal Contrastive Learning for Counterfactual Regression Over Time—0
A Causal Framework for Evaluating Deferring SystemsCode0
Synthetic Potential Outcomes and Causal Mixture Identifiability—0
SIG: Efficient Self-Interpretable Graph Neural Network for Continuous-time Dynamic GraphsCode0
Multi-CATE: Multi-Accurate Conditional Average Treatment Effect Estimation Robust to Unknown Covariate Shifts—0
Deriving Causal Order from Single-Variable Interventions: Guarantees & AlgorithmCode0
Is machine learning good or bad for the natural sciences?Code0
Smoke and Mirrors in Causal Downstream TasksCode0
A Counterfactual Analysis of the Dishonest Casino—0
Learning Invariant Causal Mechanism from Vision-Language Models—0
ProDAG: Projected Variational Inference for Directed Acyclic GraphsCode0
Exploring the use of a Large Language Model for data extraction in systematic reviews: a rapid feasibility study—0
Causal Inference with CocyclesCode0
Conformal Counterfactual Inference under Hidden Confounding—0
Argumentative Causal DiscoveryCode0
The Logic of Counterfactuals and the Epistemology of Causal Inference—0
Causality in the Can: Diet Coke's Impact on Fatness—0
Show:102550
← PrevPage 11 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