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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 161–170 of 1722 papers

Title	Date	Tasks	Status	Hype	Score
CausalEGM: a general causal inference framework by encoding generative modeling	Dec 8, 2022	Causal InferenceDecoder	CodeCode Available	1	5
CausalImages: An R Package for Causal Inference with Earth Observation, Bio-medical, and Social Science Images	Sep 30, 2023	Causal InferenceEarth Observation	CodeCode Available	1	5
Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification	Aug 19, 2021	Causal Inferencecounterfactual	CodeCode Available	1	5
Graph Out-of-Distribution Generalization via Causal Intervention	Feb 18, 2024	Causal InferenceOut-of-Distribution Generalization	CodeCode Available	1	5
causalgraph: A Python Package for Modeling, Persisting and Visualizing Causal Graphs Embedded in Knowledge Graphs	Jan 20, 2023	Causal DiscoveryCausal Inference	CodeCode Available	1	5
Hybrid Neural Networks for On-device Directional Hearing	Dec 11, 2021	Audio Source SeparationCausal Inference	CodeCode Available	1	5
A Brief Introduction to Causal Inference in Machine Learning	May 14, 2024	Causal InferenceOut-of-Distribution Generalization	CodeCode Available	1	5
Causal Incremental Graph Convolution for Recommender System Retraining	Aug 16, 2021	Causal InferenceRecommendation Systems	CodeCode Available	1	5
Causal Inference-Based Root Cause Analysis for Online Service Systems with Intervention Recognition	Jun 13, 2022	Causal InferenceFault Diagnosis	CodeCode Available	1	5
Counterfactual Reasoning for Out-of-distribution Multimodal Sentiment Analysis	Jul 24, 2022	Causal Inferencecounterfactual	CodeCode Available	1	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