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

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Showing 526–550 of 1722 papers

TitleStatusHype
Connecting Data to Mechanisms with Meta Structual Causal Model—0
C-Learner: Constrained Learning for Causal Inference and Semiparametric Statistics—0
Causal Discovery and Causal Learning for Fire Resistance Evaluation: Incorporating Domain Knowledge—0
Application of targeted maximum likelihood estimation in public health and epidemiological studies: a systematic review—0
Long-term Causal Inference via Modeling Sequential Latent Confounding—0
Time-Series K-means in Causal Inference and Mechanism Clustering for Financial Data—0
Causal Deep Reinforcement Learning Using Observational Data—0
A Causal Perspective on Loan Pricing: Investigating the Impacts of Selection Bias on Identifying Bid-Response Functions—0
Confounding-Robust Policy Improvement with Human-AI Teams—0
Causal Deep Learning—0
Causal Decision Trees—0
Application of Causal Inference to Analytical Customer Relationship Management in Banking and Insurance—0
Causal DAG Summarization (Full Version)—0
Causal DAG extraction from a library of books or videos/movies—0
A Point Process Model for Optimizing Repeated Personalized Action Delivery to Users—0
Adventures in Demand Analysis Using AI—0
Confronting Machine Learning With Financial Research—0
Constraint-Based Causal Discovery using Partial Ancestral Graphs in the presence of Cycles—0
Causal-Copilot: An Autonomous Causal Analysis Agent—0
Adventurer: Optimizing Vision Mamba Architecture Designs for Efficiency—0
Causal Coordinated Concurrent Reinforcement Learning—0
Causal Contrastive Learning for Counterfactual Regression Over Time—0
A Perspective on Gaussian Processes for Earth Observation—0
Causal Modeling with Stochastic Confounders—0
Causal Confirmation Measures: From Simpson's Paradox to COVID-19—0
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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