Latest Articles for Statistical Methods

A novel approach using optimal transport improves multivariate data comparison.

Examining how events cluster and influence each other over time.

Exploring how individual responses to interventions provide clearer insights into effectiveness.

CATS model challenges traditional approaches in time series forecasting using cross-attention.

A review of methods to handle systematic errors in observational studies.

Combining tensor completion with uncertainty quantification for better data insights.

ITEM priors improve parameter estimates in cosmology by addressing nuisance parameters.

A look at simulation-based inference and its applications in research.

LFIS offers a systematic method for sampling from complex distributions.

New methods enhance analysis of first-order iterative algorithms for improved performance.

Introducing MaCoDE, a method for creating high-quality synthetic data.

A method for predicting responses in interconnected networks using shared underlying structures.

A look at MDI-LR algorithm's efficiency in complex integration.

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.