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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 821–830 of 1722 papers

Title	Date	Tasks	Status	Hype
NESTER: An Adaptive Neurosymbolic Method for Causal Effect Estimation	Nov 8, 2022	Causal InferenceProgram Synthesis	—Unverified	0
Deep Causal Learning: Representation, Discovery and Inference	Nov 7, 2022	Causal DiscoveryCausal Inference	—Unverified	0
Evaluating Digital Tools for Sustainable Agriculture using Causal Inference	Nov 6, 2022	Causal Inference	—Unverified	0
Empirical Analysis of Model Selection for Heterogeneous Causal Effect Estimation	Nov 3, 2022	AutoMLCausal Inference	CodeCode Available	1
A Bayesian Semiparametric Method For Estimating Causal Quantile Effects	Nov 3, 2022	Causal Inferencecounterfactual	—Unverified	0
Causal Counterfactuals for Improving the Robustness of Reinforcement Learning	Nov 2, 2022	Causal Inferencereinforcement-learning	CodeCode Available	1
Propensity score models are better when post-calibrated	Nov 2, 2022	Causal Inference	CodeCode Available	0
Inference and Denoise: Causal Inference-based Neural Speech Enhancement	Nov 2, 2022	Causal InferenceSpeech Enhancement	CodeCode Available	1
CausalBench: A Large-scale Benchmark for Network Inference from Single-cell Perturbation Data	Oct 31, 2022	Causal DiscoveryCausal Inference	CodeCode Available	1
Formalizing Statistical Causality via Modal Logic	Oct 30, 2022	Causal Inference	—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