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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 Added Most Hyped Most Active Needs Verification Most Verified

Showing 501–510 of 1722 papers

Title	Date	Tasks	Status	Hype
Neural Causal Abstractions	Jan 5, 2024	Causal InferenceRepresentation Learning	CodeCode Available	0
Modular Learning of Deep Causal Generative Models for High-dimensional Causal Inference	Jan 2, 2024	Causal Inferencecounterfactual	CodeCode Available	0
Inverting estimating equations for causal inference on quantiles	Jan 2, 2024	Causal Inference	—Unverified	0
Inferring Heterogeneous Treatment Effects of Crashes on Highway Traffic: A Doubly Robust Causal Machine Learning Approach	Jan 1, 2024	Causal Inferencecounterfactual	—Unverified	0
Modeling Systemic Risk: A Time-Varying Nonparametric Causal Inference Framework	Dec 27, 2023	Causal Inference	—Unverified	0
The Challenge of Using LLMs to Simulate Human Behavior: A Causal Inference Perspective	Dec 24, 2023	Causal InferenceExperimental Design	—Unverified	0
An Explainable AI Approach to Large Language Model Assisted Causal Model Auditing and Development	Dec 23, 2023	Causal InferenceEpidemiology	—Unverified	0
Causal Forecasting for Pricing	Dec 23, 2023	Causal InferenceDecision Making	—Unverified	0
Zero-shot Causal Graph Extrapolation from Text via LLMs	Dec 22, 2023	Causal Inference	CodeCode Available	0
Invariant Anomaly Detection under Distribution Shifts: A Causal Perspective	Dec 21, 2023	Anomaly DetectionCausal Inference	CodeCode Available	1

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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