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 1601–1650 of 1722 papers

TitleStatusHype
Framework for inferring empirical causal graphs from binary data to support multidimensional poverty analysisCode0
An Efficient Approach for Optimizing the Cost-effective Individualized Treatment Rule Using Conditional Random ForestCode0
Prescriptive Process Monitoring Under Resource Constraints: A Causal Inference ApproachCode0
Matching with Text Data: An Experimental Evaluation of Methods for Matching Documents and of Measuring Match QualityCode0
Variable Importance Matching for Causal InferenceCode0
A pragmatic approach to estimating average treatment effects from EHR data: the effect of prone positioning on mechanically ventilated COVID-19 patientsCode0
Neural Network Parameter-optimization of Gaussian pmDAGsCode0
Preventing Spurious Interactions: A New Inductive Bias for Accurate Treatment Effect EstimationCode0
Ancestral Causal InferenceCode0
Causal Inference Through the Structural Causal Marginal ProblemCode0
Functional Generalized Empirical Likelihood Estimation for Conditional Moment RestrictionsCode0
GANITE: Estimation of Individualized Treatment Effects using Generative Adversarial NetsCode0
s-ID: Causal Effect Identification in a Sub-PopulationCode0
Measuring the Effect of Training Data on Deep Learning Predictions via Randomized ExperimentsCode0
Generalized Encouragement-Based Instrumental Variables for Counterfactual RegressionCode0
Measuring Variable Importance in Heterogeneous Treatment Effects with ConfidenceCode0
Be Aware of the Neighborhood Effect: Modeling Selection Bias under InterferenceCode0
Mechanism learning: Reverse causal inference in the presence of multiple unknown confounding through front-door causal bootstrappingCode0
Causal inference of brain connectivity from fMRI with ψ-Learning Incorporated Linear non-Gaussian Acyclic Model (ψ-LiNGAM)Code0
Causal Inference in Possibly Nonlinear Factor ModelsCode0
SIG: Efficient Self-Interpretable Graph Neural Network for Continuous-time Dynamic GraphsCode0
A Fast Bootstrap Algorithm for Causal Inference with Large DataCode0
DNA-SE: Towards Deep Neural-Nets Assisted Semiparametric EstimationCode0
MERLiN: Mixture Effect Recovery in Linear NetworksCode0
The Computational Curse of Big Data for Bayesian Additive Regression Trees: A Hitting Time AnalysisCode0
Weighted Tensor Completion for Time-Series Causal InferenceCode0
Using Causal Analysis for Conceptual Deep Learning ExplanationCode0
Grab the Reins of Crowds: Estimating the Effects of Crowd Movement Guidance Using Causal InferenceCode0
Gradient-Based Neural DAG LearningCode0
Granger Causal Inference in Multivariate Hawkes Processes by Minimum Message LengthCode0
Causal Inference under Outcome-Based Sampling with Monotonicity AssumptionsCode0
An Adaptive Kernel Approach to Federated Learning of Heterogeneous Causal EffectsCode0
Towards Representation Learning for Weighting Problems in Design-Based Causal InferenceCode0
ProDAG: Projected Variational Inference for Directed Acyclic GraphsCode0
Graph Neural Network Causal Explanation via Neural Causal ModelsCode0
Minimax Kernel Machine Learning for a Class of Doubly Robust Functionals with Application to Proximal Causal InferenceCode0
Causal Inference from Text: Unveiling Interactions between VariablesCode0
GST-UNet: Spatiotemporal Causal Inference with Time-Varying ConfoundersCode0
Slangvolution: A Causal Analysis of Semantic Change and Frequency Dynamics in SlangCode0
SLEM: Machine Learning for Path Modeling and Causal Inference with Super Learner Equation ModelingCode0
Adversarial Generalized Method of MomentsCode0
The Effect of Noise Level on Causal Identification with Additive Noise ModelsCode0
Harmonization with Flow-based Causal InferenceCode0
HERMES: Hybrid Error-corrector Model with inclusion of External Signals for nonstationary fashion time seriesCode0
Smoke and Mirrors in Causal Downstream TasksCode0
Heterogeneous causal effects with imperfect compliance: a Bayesian machine learning approachCode0
Rethinking recidivism through a causal lensCode0
Heterogeneous Peer Effects in the Linear Threshold ModelCode0
MissDeepCausal: Causal Inference from Incomplete Data Using Deep Latent Variable ModelsCode0
Propensity Score Alignment of Unpaired Multimodal DataCode0
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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