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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 891–900 of 1722 papers

Title	Date	Tasks	Status	Hype
Long-term Causal Effects Estimation via Latent Surrogates Representation Learning	Aug 9, 2022	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
Forecasting Algorithms for Causal Inference with Panel Data	Aug 6, 2022	Causal Inferencecounterfactual	CodeCode Available	0
Causality in cardiorespiratory signals in pediatric cardiac patients	Aug 5, 2022	Causal Inference	—Unverified	0
The Face of Affective Disorders	Aug 2, 2022	Causal InferenceDiagnostic	—Unverified	0
Deep Reinforcement Learning for Multi-Agent Interaction	Aug 2, 2022	BIG-bench Machine LearningCausal Inference	CodeCode Available	2
Tangential Wasserstein Projections	Jul 29, 2022	Causal Inference	CodeCode Available	0
Cross-Modal Causal Relational Reasoning for Event-Level Visual Question Answering	Jul 26, 2022	Causal InferenceQuestion Answering	CodeCode Available	1
Counterfactual Reasoning for Out-of-distribution Multimodal Sentiment Analysis	Jul 24, 2022	Causal Inferencecounterfactual	CodeCode Available	1
Building Human Values into Recommender Systems: An Interdisciplinary Synthesis	Jul 20, 2022	Causal InferenceEthics	—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