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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 1591–1600 of 1722 papers

Title	Date	Tasks	Status	Hype	Score
Counterfactual Invariance to Spurious Correlations in Text Classification	May 21, 2021	Causal InferenceClassification	—Unverified	0	0
Counterfactually Fair Regression with Double Machine Learning	Mar 21, 2023	Causal Inferencecounterfactual	—Unverified	0	0
Counterfactually Fair Reinforcement Learning via Sequential Data Preprocessing	Jan 10, 2025	Causal Inferencecounterfactual	—Unverified	0	0
Counterfactual Propagation for Semi-Supervised Individual Treatment Effect Estimation	May 11, 2020	Causal Inferencecounterfactual	—Unverified	0	0
Counterfactual Reasoning and Learning Systems	Sep 11, 2012	Causal Inferencecounterfactual	—Unverified	0	0
Counterfactual Representation Learning with Balancing Weights	Oct 23, 2020	Causal Inferencecounterfactual	—Unverified	0	0
Counterfactual Thinking for Long-tailed Information Extraction	Jan 1, 2021	Causal Inferencecounterfactual	—Unverified	0	0
Counting and Sampling from Markov Equivalent DAGs Using Clique Trees	Feb 5, 2018	Causal Inference	—Unverified	0	0
Covariate-Balancing-Aware Interpretable Deep Learning models for Treatment Effect Estimation	Mar 7, 2022	Additive modelsCausal Inference	—Unverified	0	0
Credit Ratings: Heterogeneous Effect on Capital Structure	Jun 27, 2024	Causal InferenceVariable Selection	—Unverified	0	0

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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