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 801–825 of 1722 papers

TitleStatusHype
A scoping review of causal methods enabling predictions under hypothetical interventions—0
DRTCI: Learning Disentangled Representations for Temporal Causal Inference—0
Epistemic Limits of Empirical Finance: Causal Reductionism and Self-Reference—0
DROID: Driver-centric Risk Object Identification—0
Error Causal inference for Multi-Fusion models—0
Establishing Causal Relationship Between Whole Slide Image Predictions and Diagnostic Evidence Subregions in Deep Learning—0
Causal Inference from Small High-dimensional Datasets—0
Causal Inference from Slowly Varying Nonstationary Processes—0
Estimating Causal Effects in Partially Directed Parametric Causal Factor Graphs—0
A Synthetic Business Cycle Approach to Counterfactual Analysis with Nonstationary Macroeconomic Data—0
Estimating Causal Effects of Text Interventions Leveraging LLMs—0
Causal Inference for Time series Analysis: Problems, Methods and Evaluation—0
Estimating causal effects with optimization-based methods: A review and empirical comparison—0
Estimating Causal Effects With Partial Covariates For Clinical Interpretability—0
Doubly Robust Off-Policy Learning on Low-Dimensional Manifolds by Deep Neural Networks—0
Causal inference for the expected number of recurrent events in the presence of a terminal event—0
Asymptotic Properties of the Distributional Synthetic Controls—0
Estimating Heterogeneous Causal Effects in the Presence of Irregular Assignment Mechanisms—0
A General Causal Inference Framework for Cross-Sectional Observational Data—0
Causal Inference for Survival Analysis—0
Online Multi-Armed Bandits with Adaptive Inference—0
Asymptotic Causal Inference—0
DoubleMLDeep: Estimation of Causal Effects with Multimodal Data—0
Causal Inference for Recommendation: Foundations, Methods and Applications—0
A Free Lunch with Influence Functions? Improving Neural Network Estimates with Concepts from Semiparametric Statistics—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