Analyzing $L^2$-Posterior Contraction Rates in Bayesian Nonparametric Regression
Published:Dec 23, 2025 16:53
•1 min read
•ArXiv
Analysis
This article likely delves into the theoretical aspects of Bayesian nonparametric regression, focusing on the convergence properties of the posterior distribution. Understanding contraction rates is crucial for assessing the performance and reliability of these models.
Key Takeaways
- •Focuses on Bayesian nonparametric regression.
- •Investigates the contraction rates of the posterior.
- •Considers Gaussian process and random series priors.
Reference
“The article's focus is on $L^2$-posterior contraction rates for specific priors.”