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 1476–1500 of 1722 papers

Title	Date	Tasks	Status
A Multi-level Neural Network for Implicit Causality Detection in Web Texts	Aug 18, 2019	Causal InferenceFeature Engineering	CodeCode Available
Optimal Estimation of Generalized Average Treatment Effects using Kernel Optimal Matching	Aug 13, 2019	Causal Inference	CodeCode Available
Transcriptional Response of SK-N-AS Cells to Methamidophos	Aug 11, 2019	Anomaly DetectionCausal Inference	—Unverified
Choosing with unknown causal information: Action-outcome probabilities for decision making can be grounded in causal models	Jul 26, 2019	Causal InferenceDecision Making	—Unverified
A neural network oracle for quantum nonlocality problems in networks	Jul 24, 2019	Causal Inference	CodeCode Available
Info Intervention	Jul 24, 2019	Causal Inferencecounterfactual	—Unverified
A discriminative approach for finding and characterizing positivity violations using decision trees	Jul 18, 2019	Causal Inferencevalid	—Unverified
Explaining Classifiers with Causal Concept Effect (CaCE)	Jul 16, 2019	Causal Inference	—Unverified
Quantifying Error in the Presence of Confounders for Causal Inference	Jul 10, 2019	Causal InferenceRepresentation Learning	—Unverified
Quantifying Confounding Bias in Neuroimaging Datasets with Causal Inference	Jul 9, 2019	Causal Inference	—Unverified
Adjustment Criteria for Recovering Causal Effects from Missing Data	Jul 2, 2019	Causal InferenceSelection bias	—Unverified
Identification In Missing Data Models Represented By Directed Acyclic Graphs	Jun 29, 2019	Causal Inference	—Unverified
Causal Inference Under Interference And Network Uncertainty	Jun 29, 2019	Causal Inference	—Unverified
Learning Causal State Representations of Partially Observable Environments	Jun 25, 2019	Causal InferenceReinforcement Learning	—Unverified
A Bayesian Solution to the M-Bias Problem	Jun 17, 2019	Causal Inference	—Unverified
Reinforcement Knowledge Graph Reasoning for Explainable Recommendation	Jun 12, 2019	Causal InferenceDecision Making	CodeCode Available
Learning Individual Causal Effects from Networked Observational Data	Jun 8, 2019	Causal Inference	CodeCode Available
Reliable Estimation of Individual Treatment Effect with Causal Information Bottleneck	Jun 7, 2019	Causal Inference	—Unverified
Adapting Neural Networks for the Estimation of Treatment Effects	Jun 5, 2019	Causal Inference	CodeCode Available
Gradient-Based Neural DAG Learning	Jun 5, 2019	Causal Inference	CodeCode Available
The Secrets of Machine Learning: Ten Things You Wish You Had Known Earlier to be More Effective at Data Analysis	Jun 4, 2019	BIG-bench Machine LearningCausal Inference	—Unverified
An Evaluation Toolkit to Guide Model Selection and Cohort Definition in Causal Inference	Jun 2, 2019	BIG-bench Machine LearningCausal Inference	CodeCode Available
Measuring and Modeling Language Change	Jun 1, 2019	Causal InferenceTwo-sample testing	—Unverified
Multiple Causes: A Causal Graphical View	May 30, 2019	Causal Inferencevalid	—Unverified
Rarely-switching linear bandits: optimization of causal effects for the real world	May 30, 2019	Causal InferenceMulti-Armed Bandits	—Unverified

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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