Tag: ad
-
Bayesian Additive Regression Trees for functional ANOVA model
Bayesian Additive Regression Trees for functional ANOVA model arXiv:2509.03317v1 Announce Type: new Abstract: Bayesian Additive Regression Trees (BART) is a powerful statistical model that leverages the strengths of Bayesian inference and regression trees. It has received significant attention for capturing complex non-linear relationships and interactions among predictors. However, the accuracy of BART often comes at…
-
Structural DID with ML: Theory, Simulation, and a Roadmap for Applied Research
Structural DID with ML: Theory, Simulation, and a Roadmap for Applied Research arXiv:2507.15899v1 Announce Type: new Abstract: Causal inference in observational panel data has become a central concern in economics,policy analysis,and the broader social sciences.To address the core contradiction where traditional difference-in-differences (DID) struggles with high-dimensional confounding variables in observational panel data,while machine learning (ML)…
-
Bridging Unsupervised and Semi-Supervised Anomaly Detection: A Theoretically-Grounded and Practical Framework with Synthetic Anomalies
Bridging Unsupervised and Semi-Supervised Anomaly Detection: A Theoretically-Grounded and Practical Framework with Synthetic Anomalies arXiv:2506.13955v1 Announce Type: new Abstract: Anomaly detection (AD) is a critical task across domains such as cybersecurity and healthcare. In the unsupervised setting, an effective and theoretically-grounded principle is to train classifiers to distinguish normal data from (synthetic) anomalies. We extend…