Latest Articles for Statistical Methods

A novel approach to improve low-resolution images using stochastic methods.

Flow matching offers a new way to generate data samples efficiently.

New methods for privacy-preserving collaboration in vertical federated learning.

This article presents a method to improve handling of missing data.

A new method improves data privacy for discrete data analysis.

New methods improve the efficiency and reliability of clinical trials.

Enhancing the representativeness of sortition in democratic processes through new methods.

A new method enhances solution quality in medical imaging challenges.

Introducing a new approach for efficient sampling from complex distributions.

A new method enhances the accuracy of Bayesian evidence calculation in cosmology.

New method improves federated learning while protecting user privacy.

Study examines methods to test changes in factor models using eigenvalues and eigenvectors.

A new method improves the estimation of weak and strong factors in data.

Improving prediction accuracy through innovative loss aggregation methods.

A new method for better economic predictions using latent factors and kernel techniques.

Understanding treatment impacts while accounting for network interference.

An overview of SVM techniques for handling class imbalance in machine learning.

This article addresses the difficulties in evaluating Bayesian Causal Discovery methods.

A method to improve analysis of distributed, high-dimensional data in various fields.

A new method creates reliable prediction intervals using diverse data while ensuring privacy.

This article presents a novel approach to predicting time series data in finance.

New framework improves probability computations in complex datasets for various fields.

A new MCMC method improves efficiency in complex data analysis.

New protocols reduce sample complexity for mixed quantum states.

A clear look at shift-share designs and their role in economic studies.

This study investigates the limits of accuracy and robustness in machine learning models.

Introducing Diffusion Paths for efficient OOD detection using a single model.

A new method for verifying the common trend assumption in treatment effect studies.

A new R package for functional semiparametric regression and data analysis.

Examining how stochastic models help in predicting infectious disease spread.

A study on methods for safe synthetic data that maintains privacy and usefulness.

Introducing autophagy penalized likelihood estimation to address bias in AI models.

MultiSuSiE improves genetic variant identification across diverse populations.

A new method tackles duplicated data challenges in spatial point process models.

A look at the role of non-probability data in modern statistical methods.

An exploration of algorithmic stability and testing limitations.

New methods for certifying anti-concentration in data distributions enhance machine learning applications.

A look at Differentiable Annealed Importance Sampling and its benefits in machine learning.

A look at how randomized quasi-Monte Carlo methods estimate integrals under various conditions.

This study explores how teachers influence each other's beliefs and practices.