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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 1671–1680 of 1722 papers

Title	Date	Tasks	Status	Hype
Adversarial Balancing-based Representation Learning for Causal Effect Inference with Observational Data	Apr 30, 2019	Causal InferenceRepresentation Learning	CodeCode Available	0
Modular Learning of Deep Causal Generative Models for High-dimensional Causal Inference	Jan 2, 2024	Causal Inferencecounterfactual	CodeCode Available	0
Spike-based causal inference for weight alignment	Oct 3, 2019	Causal InferenceEconometrics	CodeCode Available	0
Causal Inference for Human-Language Model Collaboration	Mar 30, 2024	Causal Inferencecounterfactual	CodeCode Available	0
Hyperparameter Tuning and Model Evaluation in Causal Effect Estimation	Mar 2, 2023	Causal InferenceModel Selection	CodeCode Available	0
Adaptive Nonparametric Perturbations of Parametric Bayesian Models	Dec 14, 2024	Bayesian InferenceCausal Inference	CodeCode Available	0
Adapting Neural Networks for the Estimation of Treatment Effects	Jun 5, 2019	Causal Inference	CodeCode Available	0
MPEG: A Multi-Perspective Enhanced Graph Attention Network for Causal Emotion Entailment in Conversations	Sep 15, 2023	Causal Emotion EntailmentCausal Inference	CodeCode Available	0
Zero-shot Causal Graph Extrapolation from Text via LLMs	Dec 22, 2023	Causal Inference	CodeCode Available	0
Identifiable causal inference with noisy treatment and no side information	Jun 18, 2023	Causal InferenceEconometrics	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