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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 171–180 of 1722 papers

Title	Date	Tasks	Status	Hype
Beyond Reward Hacking: Causal Rewards for Large Language Model Alignment	Jan 16, 2025	Causal Inferencecounterfactual	CodeCode Available	4
Kolmogorov-Arnold Networks for Time Series Granger Causality Inference	Jan 15, 2025	Causal InferenceKolmogorov-Arnold Networks	—Unverified	0
ML-assisted Randomization Tests for Detecting Treatment Effects in A/B Experiments	Jan 13, 2025	Causal InferenceDecision Making	—Unverified	0
MECD+: Unlocking Event-Level Causal Graph Discovery for Video Reasoning	Jan 13, 2025	Causal DiscoveryCausal Inference	CodeCode Available	1
Doubly Robust Inference on Causal Derivative Effects for Continuous Treatments	Jan 12, 2025	Causal Inference	CodeCode Available	0
Causal Claims in Economics	Jan 12, 2025	Causal InferenceKnowledge Graphs	—Unverified	0
Automatic Double Reinforcement Learning in Semiparametric Markov Decision Processes with Applications to Long-Term Causal Inference	Jan 12, 2025	Causal InferenceDimensionality Reduction	—Unverified	0
Do we actually understand the impact of renewables on electricity prices? A causal inference approach	Jan 10, 2025	Causal Inference	CodeCode Available	2
Counterfactually Fair Reinforcement Learning via Sequential Data Preprocessing	Jan 10, 2025	Causal Inferencecounterfactual	—Unverified	0
Explainable Federated Bayesian Causal Inference and Its Application in Advanced Manufacturing	Jan 10, 2025	Causal InferenceExplainable artificial intelligence	CodeCode Available	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