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 1601–1625 of 1722 papers

TitleStatusHype
On the difference between building and extracting patterns: a causal analysis of deep generative models.—0
GANITE: Estimation of Individualized Treatment Effects using Generative Adversarial NetsCode0
Estimation and Inference on Heterogeneous Treatment Effects in High-Dimensional Dynamic Panels under Weak Dependence—0
An Exact and Robust Conformal Inference Method for Counterfactual and Synthetic ControlsCode0
Bayesian Nonparametric Causal Inference: Information Rates and Learning Algorithms—0
Obtaining Accurate Probabilistic Causal Inference by Post-Processing Calibration—0
Interventions over Predictions: Reframing the Ethical Debate for Actuarial Risk Assessment—0
RNN-based counterfactual prediction, with an application to homestead policy and public schoolingCode0
Permutation-based Causal Inference Algorithms with Interventions—0
Causal nearest neighbor rules for optimal treatment regimes—0
Estimation Considerations in Contextual Bandits—0
Orthogonal Machine Learning: Power and LimitationsCode0
Synth-Validation: Selecting the Best Causal Inference Method for a Given Dataset—0
Causal Rule Sets for Identifying Subgroups with Enhanced Treatment Effect—0
A Framework for Inferring Causality from Multi-Relational Observational Data using Conditional Independence—0
Uncertainty Assessment and False Discovery Rate Control in High-Dimensional Granger Causal Inference—0
Feature Selection as Causal Inference: Experiments with Text Classification—0
The Inflation Technique Completely Solves the Causal Compatibility Problem—0
Domain Adaptation by Using Causal Inference to Predict Invariant Conditional DistributionsCode0
FLAME: A Fast Large-scale Almost Matching Exactly Approach to Causal Inference—0
On Adaptive Propensity Score Truncation in Causal InferenceCode0
Learning linear structural equation models in polynomial time and sample complexity—0
Fast Restricted Causal Inference—0
Automated versus do-it-yourself methods for causal inference: Lessons learned from a data analysis competition—0
Restricted Causal Inference Algorithm—0
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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