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

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Showing 801–850 of 1722 papers

TitleStatusHype
Intervention Generalization: A View from Factor Graph Models—0
Contagion Effect Estimation Using Proximal Embeddings—0
Individual Causal Inference Using Panel Data With Multiple Outcomes—0
Behavioral Causal Inference—0
Point Cloud Completion Guided by Prior Knowledge via Causal Inference—0
Inferring Individual Direct Causal Effects Under Heterogeneous Peer InfluenceCode0
Controlling Learned Effects to Reduce Spurious Correlations in Text Classifiers—0
T2TD: Text-3D Generation Model based on Prior Knowledge Guidance—0
Dynamic Inter-treatment Information Sharing for Individualized Treatment Effects EstimationCode0
Neuroevolutionary representations for learning heterogeneous treatment effectsCode0
Operationalizing Counterfactual Metrics: Incentives, Ranking, and Information Asymmetry—0
Covariate balancing using the integral probability metric for causal inferenceCode0
Causality-Aided Trade-off Analysis for Machine Learning Fairness—0
The Decaying Missing-at-Random Framework: Model Doubly Robust Causal Inference with Partially Labeled Data—0
How Fragile is Relation Extraction under Entity Replacements?Code0
uCTRL: Unbiased Contrastive Representation Learning via Alignment and Uniformity for Collaborative FilteringCode0
Estimation Beyond Data Reweighting: Kernel Method of MomentsCode0
A Survey on Causal Discovery: Theory and Practice—0
The Impact of Missing Data on Causal Discovery: A Multicentric Clinical Study—0
Counterfactually Comparing Abstaining ClassifiersCode0
The Hardness of Reasoning about Probabilities and Causality—0
Artificial intelligence to advance Earth observation: : A review of models, recent trends, and pathways forward—0
A Causal Inference Framework for Leveraging External Controls in Hybrid Trials—0
Integrating Nearest Neighbors with Neural Network Models for Treatment Effect Estimation—0
Reinterpreting causal discovery as the task of predicting unobserved joint statistics—0
Axiomatization of Interventional Probability Distributions—0
The Fundamental Limits of Structure-Agnostic Functional Estimation—0
Causal Discovery with Stage Variables for Health Time Series—0
String Diagrams with Factorized Densities—0
Understand Waiting Time in Transaction Fee Mechanism: An Interdisciplinary PerspectiveCode0
CausalAPM: Generalizable Literal Disentanglement for NLU Debiasing—0
Efficient estimation of weighted cumulative treatment effects by double/debiased machine learning—0
Double and Single Descent in Causal Inference with an Application to High-Dimensional Synthetic ControlCode0
An Efficient Doubly-Robust Test for the Kernel Treatment Effect—0
Causal Semantic Communication for Digital Twins: A Generalizable Imitation Learning Approach—0
Causal fault localisation in dataflow systemsCode0
Causal Effect Estimation with Variational AutoEncoder and the Front Door Criterion—0
Debiasing Conditional Stochastic Optimization—0
METAM: Goal-Oriented Data Discovery—0
Adjustment with Many Regressors Under Covariate-Adaptive Randomizations—0
Compositional Probabilistic and Causal Inference using Tractable Circuit ModelsCode0
Causal models in string diagrams—0
Predictive Incrementality by Experimentation (PIE) for Ad Measurement—0
Bayesian Causal Inference in Doubly Gaussian DAG-probit Models—0
Partial Identification of Causal Effects Using Proxy Variables—0
Bridging Nations: Quantifying the Role of Multilinguals in Communication on Social MediaCode0
Data AUDIT: Identifying Attribute Utility- and Detectability-Induced Bias in Task Models—0
A step towards the applicability of algorithms based on invariant causal learning on observational data—0
Matched Machine Learning: A Generalized Framework for Treatment Effect Inference With Learned Metrics—0
TSCI: two stage curvature identification for causal inference with invalid instruments—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