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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 851–860 of 1722 papers

Title	Date	Tasks	Status	Hype
Distilling Causal Effect from Miscellaneous Other-Class for Continual Named Entity Recognition	Oct 8, 2022	Causal InferenceContinual Learning	CodeCode Available	1
LLMEffiChecker: Understanding and Testing Efficiency Degradation of Large Language Models	Oct 7, 2022	Causal InferenceMachine Translation	CodeCode Available	0
FAST: Improving Controllability for Text Generation with Feedback Aware Self-Training	Oct 6, 2022	AttributeCausal Inference	—Unverified	0
Text-driven Video Prediction	Oct 6, 2022	Causal InferencePrediction	—Unverified	0
Causal Inference for Chatting Handoff	Oct 6, 2022	Causal InferenceChatbot	CodeCode Available	1
Transfer Learning for Individual Treatment Effect Estimation	Oct 1, 2022	Causal Inferencecounterfactual	—Unverified	0
Predicting Cellular Responses with Variational Causal Inference and Refined Relational Information	Sep 30, 2022	Causal Inferencecounterfactual	CodeCode Available	1
Causal Inference via Nonlinear Variable Decorrelation for Healthcare Applications	Sep 29, 2022	Causal Inferenceparameter estimation	—Unverified	0
Causal inference in drug discovery and development	Sep 29, 2022	Causal InferenceDecision Making	—Unverified	0
Causal Proxy Models for Concept-Based Model Explanations	Sep 28, 2022	Causal Inferencecounterfactual	CodeCode Available	1

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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