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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 481–490 of 1722 papers

Title	Date	Tasks	Status	Hype	Score
A Multi-level Neural Network for Implicit Causality Detection in Web Texts	Aug 18, 2019	Causal InferenceFeature Engineering	CodeCode Available	0	5
Causally Denoise Word Embeddings Using Half-Sibling Regression	Nov 24, 2019	Causal Inferenceregression	CodeCode Available	0	5
Ancestral Causal Inference	Jun 22, 2016	Causal DiscoveryCausal Inference	CodeCode Available	0	5
Recovering the Graph Underlying Networked Dynamical Systems under Partial Observability: A Deep Learning Approach	Aug 8, 2022	Causal InferenceTime Series	CodeCode Available	0	5
Causally motivated Shortcut Removal Using Auxiliary Labels	May 13, 2021	Causal InferenceDisentanglement	CodeCode Available	0	5
Reframed GES with a Neural Conditional Dependence Measure	Jun 17, 2022	Causal DiscoveryCausal Inference	CodeCode Available	0	5
Adaptive Nonparametric Perturbations of Parametric Bayesian Models	Dec 14, 2024	Bayesian InferenceCausal Inference	CodeCode Available	0	5
Removing systematic errors for exoplanet search via latent causes	May 12, 2015	AstronomyCausal Inference	CodeCode Available	0	5
A Normative Theory for Causal Inference and Bayes Factor Computation in Neural Circuits	Dec 1, 2019	Causal InferenceModel Selection	CodeCode Available	0	5
Challenges of Using Text Classifiers for Causal Inference	Oct 1, 2018	Causal InferenceDecision Making	CodeCode Available	0	5

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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