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

Showing 11761200 of 1722 papers

TitleStatusHype
From Text to Treatment Effects: A Meta-Learning Approach to Handling Text-Based Confounding0
From What Ifs to Insights: Counterfactuals in Causal Inference vs. Explainable AI0
GCF: Generalized Causal Forest for Heterogeneous Treatment Effect Estimation in Online Marketplace0
Generalization bound for estimating causal effects from observational network data0
Generalized Kernel Ridge Regression for Causal Inference with Missing-at-Random Sample Selection0
Kernel methods for long term dose response curves0
Generalized Optimal Matching Methods for Causal Inference0
General Transportability of Soft Interventions: Completeness Results0
Generating High-Fidelity Privacy-Conscious Synthetic Patient Data for Causal Effect Estimation with Multiple Treatments0
Generating Synthetic Text Data to Evaluate Causal Inference Methods0
Generative Intervention Models for Causal Perturbation Modeling0
Generator Identification for Linear SDEs with Additive and Multiplicative Noise0
Geometry-Aware Normalizing Wasserstein Flows for Optimal Causal Inference0
GP CaKe: Effective brain connectivity with causal kernels0
Granger Causality for Compressively Sensed Sparse Signals0
Graph Disentangle Causal Model: Enhancing Causal Inference in Networked Observational Data0
Graph Infomax Adversarial Learning for Treatment Effect Estimation with Networked Observational Data0
Graph Neural Networks: Theory for Estimation with Application on Network Heterogeneity0
G-Transformer: Counterfactual Outcome Prediction under Dynamic and Time-varying Treatment Regimes0
Guiding Treatment Strategies: The Role of Adjuvant Anti-Her2 Neu Therapy and Skin/Nipple Involvement in Local Recurrence-Free Survival in Breast Cancer Patients0
Half-AVAE: Adversarial-Enhanced Factorized and Structured Encoder-Free VAE for Underdetermined Independent Component Analysis0
Half-VAE: An Encoder-Free VAE to Bypass Explicit Inverse Mapping0
Estimating Heterogeneous Causal Effect of Polysubstance Usage on Drug Overdose from Large-Scale Electronic Health Record0
Heterogeneous Effects of Software Patches in a Multiplayer Online Battle Arena Game0
Heterogeneous Treatment Effect Estimation using machine learning for Healthcare application: tutorial and benchmark0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Random ForestAverage Treatment Effect Error0.96Unverified
2Balancing Linear RegressionAverage Treatment Effect Error0.93Unverified
3k-NNAverage Treatment Effect Error0.79Unverified
4CEVAEAverage Treatment Effect Error0.46Unverified
5Balancing Neural NetworkAverage Treatment Effect Error0.42Unverified
6Causal ForestAverage Treatment Effect Error0.4Unverified
7BCAUS DRAverage Treatment Effect Error0.29Unverified
8TARNetAverage Treatment Effect Error0.28Unverified
9Counterfactual Regression + WASSAverage Treatment Effect Error0.27Unverified
10MTDL-KNNAverage Treatment Effect Error0.23Unverified
#ModelMetricClaimedVerifiedStatus
1CFR WASSAverage Treatment Effect on the Treated Error0.09Unverified
2CFR MMDAverage Treatment Effect on the Treated Error0.08Unverified
3BARTAverage Treatment Effect on the Treated Error0.08Unverified
4GANITEAverage Treatment Effect on the Treated Error0.06Unverified
5BCAUSSAverage Treatment Effect on the Treated Error0.05Unverified
#ModelMetricClaimedVerifiedStatus
1BARTAverage Treatment Effect Error0.34Unverified
2OLS with separate regressors for each treatmentAverage Treatment Effect Error0.31Unverified
3Average Treatment Effect Error-0.23Unverified