SOTAVerified

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 AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1001–1025 of 1722 papers

TitleStatusHype
Learning and Evaluating Graph Neural Network Explanations based on Counterfactual and Factual ReasoningCode1
Long-term Causal Inference Under Persistent Confounding via Data CombinationCode0
Reinforcement Learning in the Wild: Scalable RL Dispatching Algorithm Deployed in Ridehailing Marketplace—0
Benign-Overfitting in Conditional Average Treatment Effect Prediction with Linear Regression—0
Validating Causal Inference Methods—0
HERMES: Hybrid Error-corrector Model with inclusion of External Signals for nonstationary fashion time seriesCode0
Targeted-BEHRT: Deep learning for observational causal inference on longitudinal electronic health recordsCode1
Evaluation Methods and Measures for Causal Learning Algorithms—0
Causal Inference Using Tractable Circuits—0
Deep End-to-end Causal Inference—0
Causal Inference Through the Structural Causal Marginal ProblemCode0
Some Reflections on Drawing Causal Inference using Textual Data: Parallels Between Human Subjects and Organized Texts—0
ROCK: Causal Inference Principles for Reasoning about Commonsense CausalityCode1
Unifying Pairwise Interactions in Complex DynamicsCode2
Heterogeneous Peer Effects in the Linear Threshold ModelCode0
Combining Experimental and Observational Data for Identification and Estimation of Long-Term Causal Effects—0
Promises and Challenges of Causality for Ethical Machine Learning—0
Learning Resource Allocation Policies from Observational Data with an Application to Homeless Services Delivery—0
Time-Series K-means in Causal Inference and Mechanism Clustering for Financial Data—0
Symbiotic bacterial network structure involved in carbon and nitrogen metabolism of wood-utilizing insect larvae—0
A Causal Lens for Controllable Text Generation—0
Unicorn: Reasoning about Configurable System Performance through the lens of CausalityCode1
DRTCI: Learning Disentangled Representations for Temporal Causal Inference—0
On the Opportunity of Causal Learning in Recommendation Systems: Foundation, Estimation, Prediction and Challenges—0
XLTime: A Cross-Lingual Knowledge Transfer Framework for Temporal Expression Extraction—0
Show:102550
← PrevPage 41 of 69Next →
All datasetsIHDPJobsIDHP

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Random ForestAverage Treatment Effect Error0.96—Unverified
2Balancing Linear RegressionAverage Treatment Effect Error0.93—Unverified
3k-NNAverage Treatment Effect Error0.79—Unverified
4CEVAEAverage Treatment Effect Error0.46—Unverified
5Balancing Neural NetworkAverage Treatment Effect Error0.42—Unverified
6Causal ForestAverage Treatment Effect Error0.4—Unverified
7BCAUS DRAverage Treatment Effect Error0.29—Unverified
8TARNetAverage Treatment Effect Error0.28—Unverified
9Counterfactual Regression + WASSAverage Treatment Effect Error0.27—Unverified
10MTDL-KNNAverage Treatment Effect Error0.23—Unverified
#ModelMetricClaimedVerifiedStatus
1CFR WASSAverage Treatment Effect on the Treated Error0.09—Unverified
2CFR MMDAverage Treatment Effect on the Treated Error0.08—Unverified
3BARTAverage Treatment Effect on the Treated Error0.08—Unverified
4GANITEAverage Treatment Effect on the Treated Error0.06—Unverified
5BCAUSSAverage Treatment Effect on the Treated Error0.05—Unverified
#ModelMetricClaimedVerifiedStatus
1BARTAverage Treatment Effect Error0.34—Unverified
2OLS with separate regressors for each treatmentAverage Treatment Effect Error0.31—Unverified
3Average Treatment Effect Error-0.23—Unverified