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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 1701–1710 of 1722 papers

Title	Date	Tasks	Status	Hype
Theoretical Impediments to Machine Learning With Seven Sparks from the Causal Revolution	Jan 11, 2018	BIG-bench Machine LearningCausal Inference	CodeCode Available	0
What's the Harm? Sharp Bounds on the Fraction Negatively Affected by Treatment	May 20, 2022	Causal InferenceFairness	CodeCode Available	0
Reconciling Predictive Multiplicity in Practice	Jan 27, 2025	Causal InferenceFairness	CodeCode Available	0
Fair Decisions Despite Imperfect Predictions	Feb 8, 2019	Causal InferenceDecision Making	CodeCode Available	0
Approaching an unknown communication system by latent space exploration and causal inference	Mar 20, 2023	Causal InferenceDisentanglement	CodeCode Available	0
Neural Causal Abstractions	Jan 5, 2024	Causal InferenceRepresentation Learning	CodeCode Available	0
When Causal Intervention Meets Adversarial Examples and Image Masking for Deep Neural Networks	Feb 9, 2019	Causal InferenceVisual Reasoning	CodeCode Available	0
Neural Score Matching for High-Dimensional Causal Inference	Mar 1, 2022	Causal InferenceVocal Bursts Intensity Prediction	CodeCode Available	0
Individualised Treatment Effects Estimation with Composite Treatments and Composite Outcomes	Feb 12, 2025	Causal InferenceMarketing	CodeCode Available	0
Recovering the Graph Underlying Networked Dynamical Systems under Partial Observability: A Deep Learning Approach	Aug 8, 2022	Causal InferenceTime Series	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