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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 1151–1200 of 1722 papers

TitleStatusHype
End-to-End Balancing for Causal Continuous Treatment-Effect Estimation—0
Towards Unbiased Visual Emotion Recognition via Causal InterventionCode1
Federated Causal Inference in Heterogeneous Observational DataCode0
CausalBERT: Injecting Causal Knowledge Into Pre-trained Models with Minimal Supervision—0
Causal Inference Struggles with Agency on Online Platforms—0
A Topological Perspective on Causal Inference—0
Auto IV: Counterfactual Prediction via Automatic Instrumental Variable DecompositionCode1
Using Causal Analysis for Conceptual Deep Learning ExplanationCode0
Machine Learning for Financial Forecasting, Planning and Analysis: Recent Developments and Pitfalls—0
Algorithmic Causal Effect Identification with causaleffectCode1
Crowd Sensing and Living Lab Outdoor Experimentation Made Easy—0
Causal affect prediction model using a facial image sequenceCode0
CausalRec: Causal Inference for Visual Debiasing in Visually-Aware RecommendationCode0
Causal Inference with Corrupted Data: Measurement Error, Missing Values, Discretization, and Differential Privacy—0
Spatiotemporal information conversion machine for time-series predictionCode1
The Causal-Neural Connection: Expressiveness, Learnability, and InferenceCode1
Causal Reinforcement Learning using Observational and Interventional DataCode1
DROID: Driver-centric Risk Object Identification—0
Finding Valid Adjustments under Non-ignorability with Minimal DAG KnowledgeCode0
Robust and Heterogenous Odds Ratio: Estimating Price Sensitivity for Unbought Items—0
Interventional Video Grounding with Dual Contrastive LearningCode0
Stratified Learning: A General-Purpose Statistical Method for Improved Learning under Covariate Shift—0
Experimentally testable whole brain manifolds that recapitulate behavior—0
Machine learning in the social and health sciences—0
CausalNLP: A Practical Toolkit for Causal Inference with TextCode1
Variational Causal Networks: Approximate Bayesian Inference over Causal StructuresCode1
Harmonization with Flow-based Causal InferenceCode0
Conterfactual Generative Zero-Shot Semantic Segmentation—0
Context-Specific Causal Discovery for Categorical Data Using Staged Trees—0
BayesIMP: Uncertainty Quantification for Causal Data Fusion—0
Graph Infomax Adversarial Learning for Treatment Effect Estimation with Networked Observational Data—0
Learning Treatment Effects in Panels with General Intervention PatternsCode0
Learning from Counterfactual Links for Link PredictionCode1
Error Causal inference for Multi-Fusion models—0
Counterfactual Invariance to Spurious Correlations: Why and How to Pass Stress Tests—0
Federated Estimation of Causal Effects from Observational DataCode1
Adaptive Multi-Source Causal Inference—0
Stochastic Intervention for Causal Inference via Reinforcement Learning—0
Stochastic Intervention for Causal Effect Estimation—0
Counterfactual Invariance to Spurious Correlations in Text Classification—0
Identifying and Estimating Causal Effects under Weak Overlap by Generative Prognostic Model—0
Variational Causal Autoencoder for Interventional and Counterfactual Queries—0
Choice Set Confounding in Discrete ChoiceCode0
Be Causal: De-biasing Social Network Confounding in Recommendation—0
Estimating Heterogeneous Causal Effect of Polysubstance Usage on Drug Overdose from Large-Scale Electronic Health Record—0
Causally motivated Shortcut Removal Using Auxiliary LabelsCode0
Causal Inference in medicine and in health policy, a summary—0
The Local Approach to Causal Inference under Network Interference—0
An Influence-based Approach for Root Cause Alarm Discovery in Telecom NetworksCode1
Proximal Learning for Individualized Treatment Regimes Under Unmeasured Confounding—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