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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 51–60 of 1722 papers

Title	Date	Tasks	Status	Hype
PO-Flow: Flow-based Generative Models for Sampling Potential Outcomes and Counterfactuals	May 21, 2025	Causal Inferencecounterfactual	—Unverified	0
Toward Informed AV Decision-Making: Computational Model of Well-being and Trust in Mobility	May 21, 2025	Causal InferenceDecision Making	CodeCode Available	0
Towards a Science of Causal Interpretability in Deep Learning for Software Engineering	May 21, 2025	Causal InferenceCode Generation	—Unverified	0
Cooperative Causal GraphSAGE	May 20, 2025	Causal InferenceGraph Neural Network	—Unverified	0
Assimilative Causal Inference	May 20, 2025	Causal InferenceTime Series	—Unverified	0
Causal Cartographer: From Mapping to Reasoning Over Counterfactual Worlds	May 20, 2025	Causal Inferencecounterfactual	CodeCode Available	0
APEX: Empowering LLMs with Physics-Based Task Planning for Real-time Insight	May 20, 2025	Causal InferenceDecision Making	CodeCode Available	0
Ice Cream Doesn't Cause Drowning: Benchmarking LLMs Against Statistical Pitfalls in Causal Inference	May 19, 2025	BenchmarkingCausal Inference	—Unverified	0
Machine learning the first stage in 2SLS: Practical guidance from bias decomposition and simulation	May 19, 2025	Causal InferencePrediction	—Unverified	0
SurveillanceVQA-589K: A Benchmark for Comprehensive Surveillance Video-Language Understanding with Large Models	May 19, 2025	Causal InferenceDecision Making	—Unverified	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