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 Added Most Hyped Most Active Needs Verification Most Verified

Showing 976–1000 of 1722 papers

Title	Date	Tasks	Status
Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data	Mar 29, 2022	Causal DiscoveryCausal Inference	CodeCode Available
From Intervention to Domain Transportation: A Novel Perspective to Optimize Recommendation	Mar 26, 2022	Causal InferenceInformation Retrieval	—Unverified
Tutorial: Modern Theoretical Tools for Understanding and Designing Next-generation Information Retrieval System	Mar 26, 2022	Causal InferenceDecision Making	—Unverified
Robustness Against Weak or Invalid Instruments: Exploring Nonlinear Treatment Models with Machine Learning	Mar 24, 2022	BIG-bench Machine LearningCausal Inference	CodeCode Available
GCF: Generalized Causal Forest for Heterogeneous Treatment Effect Estimation in Online Marketplace	Mar 21, 2022	Causal InferenceDecision Making	—Unverified
Deep Multi-Modal Structural Equations For Causal Effect Estimation With Unstructured Proxies	Mar 18, 2022	Causal InferenceTime Series Analysis	—Unverified
The worst of both worlds: A comparative analysis of errors in learning from data in psychology and machine learning	Mar 12, 2022	Causal InferenceInductive Learning	—Unverified
Identifiability of Causal-based Fairness Notions: A State of the Art	Mar 11, 2022	BIG-bench Machine LearningCausal Inference	—Unverified
Multi-Task Adversarial Learning for Treatment Effect Estimation in Basket Trials	Mar 10, 2022	Causal Inferencecounterfactual	—Unverified
Effects of Epileptiform Activity on Discharge Outcome in Critically Ill Patients	Mar 9, 2022	Causal InferenceDecision Making	—Unverified
Slangvolution: A Causal Analysis of Semantic Change and Frequency Dynamics in Slang	Mar 9, 2022	Causal DiscoveryCausal Inference	CodeCode Available
Covariate-Balancing-Aware Interpretable Deep Learning models for Treatment Effect Estimation	Mar 7, 2022	Additive modelsCausal Inference	—Unverified
Reinforcement Learning in Modern Biostatistics: Constructing Optimal Adaptive Interventions	Mar 4, 2022	Causal InferenceDecision Making	—Unverified
The Cost of Influence: How Gifts to Physicians Shape Prescriptions and Drug Costs	Mar 3, 2022	Causal Inference	—Unverified
Neural Score Matching for High-Dimensional Causal Inference	Mar 1, 2022	Causal InferenceVocal Bursts Intensity Prediction	CodeCode Available
Estimating causal effects with optimization-based methods: A review and empirical comparison	Feb 28, 2022	Causal Inference	—Unverified
Off-Policy Evaluation with Policy-Dependent Optimization Response	Feb 25, 2022	Causal InferenceDecision Making	—Unverified
Causal discovery for observational sciences using supervised machine learning	Feb 25, 2022	BIG-bench Machine LearningCausal Discovery	CodeCode Available
Predicting the impact of treatments over time with uncertainty aware neural differential equations	Feb 24, 2022	Causal Inferencecounterfactual	CodeCode Available
A Semi-Synthetic Dataset Generation Framework for Causal Inference in Recommender Systems	Feb 23, 2022	Causal InferenceDataset Generation	CodeCode Available
Partial Identification with Noisy Covariates: A Robust Optimization Approach	Feb 22, 2022	Causal Inference	—Unverified
Learning Infomax and Domain-Independent Representations for Causal Effect Inference with Real-World Data	Feb 22, 2022	Causal InferenceRepresentation Learning	—Unverified
Learning Causal Overhypotheses through Exploration in Children and Computational Models	Feb 21, 2022	Causal InferenceEfficient Exploration	—Unverified
A Free Lunch with Influence Functions? Improving Neural Network Estimates with Concepts from Semiparametric Statistics	Feb 18, 2022	Causal Inferenceparameter estimation	—Unverified
Counterfactual Analysis of the Impact of the IMF Program on Child Poverty in the Global-South Region using Causal-Graphical Normalizing Flows	Feb 17, 2022	Causal Inferencecounterfactual	—Unverified

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All datasets IHDP Jobs IDHP

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Random Forest	Average Treatment Effect Error	0.96	—	Unverified
2	Balancing Linear Regression	Average Treatment Effect Error	0.93	—	Unverified
3	k-NN	Average Treatment Effect Error	0.79	—	Unverified
4	CEVAE	Average Treatment Effect Error	0.46	—	Unverified
5	Balancing Neural Network	Average Treatment Effect Error	0.42	—	Unverified
6	Causal Forest	Average Treatment Effect Error	0.4	—	Unverified
7	BCAUS DR	Average Treatment Effect Error	0.29	—	Unverified
8	TARNet	Average Treatment Effect Error	0.28	—	Unverified
9	Counterfactual Regression + WASS	Average Treatment Effect Error	0.27	—	Unverified
10	MTDL-KNN	Average Treatment Effect Error	0.23	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	CFR WASS	Average Treatment Effect on the Treated Error	0.09	—	Unverified
2	CFR MMD	Average Treatment Effect on the Treated Error	0.08	—	Unverified
3	BART	Average Treatment Effect on the Treated Error	0.08	—	Unverified
4	GANITE	Average Treatment Effect on the Treated Error	0.06	—	Unverified
5	BCAUSS	Average Treatment Effect on the Treated Error	0.05	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	BART	Average Treatment Effect Error	0.34	—	Unverified
2	OLS with separate regressors for each treatment	Average Treatment Effect Error	0.31	—	Unverified
3		Average Treatment Effect Error	-0.23	—	Unverified