Statistics

Examining how stochastic models help in predicting infectious disease spread.

A new watermarking method aids in identifying synthetic tabular data.

New normalization methods improve spatial data predictions and analysis efficiency.

New methods improve the search for distant exoplanets through advanced data analysis.

A new method enhances brain imaging for better accuracy and efficiency.

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

New methods enhance prediction accuracy and fairness in healthcare outcomes.

Analyzing the link between pollution and rising temperatures for effective policy action.

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

Examining how stochastic models help in predicting infectious disease spread.

New normalization methods improve spatial data predictions and analysis efficiency.

A method to create data samples based on specific conditions using diffusion models.

New approaches enhance data sampling from complex distributions in statistics and machine learning.

This paper proposes using reinforcement learning to enhance adaptive MCMC algorithms.

New online methods improve functional data analysis for real-world applications.

A look into advanced techniques for better data assimilation and filtering.

Introducing EBARS for optimal knot selection in multivariate spline regression.

Effective methods to manage noisy labels in high-dimensional data for better classification.

This study examines how future predictions enhance online classification performance.

A new framework for creating reliable and accurate machine learning classifiers.

Examining how algorithms can protect privacy while optimizing decisions in personalized medicine.

CViT merges operator learning with conditioned neural fields for improved scientific modeling.

This research tackles oversmoothing in graph convolutions to improve node classification accuracy.

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

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

Examining issues with data handling in scRNA-seq gene expression studies.

Examining how stochastic models help in predicting infectious disease spread.

Introducing EBARS for optimal knot selection in multivariate spline regression.

This article discusses a new framework for kernel testing in complex data analysis.

A new method for analyzing spatio-temporal data across various fields.

New methods improve brain image data analysis using manifold learning techniques.

How organizations can keep AI models relevant and accurate.

A look at how covariate adjustment clarifies research findings by managing confounding variables.

A method allowing adaptive statistical analysis without rigid model assumptions.

A new approach to boxplots ensures data privacy while maintaining insightful analysis.

This research develops methods for fair resource allocation despite limited user feedback.

A look into how the estimand framework improves clinical trial analysis.

A fresh approach to understanding complex human connections through fuzzy social network analysis.

A study on how Park-and-Ride can reduce congestion and emissions.

Information significantly impacts decision-making processes across various fields.

This article discusses a new framework for kernel testing in complex data analysis.

A new method for analyzing spatio-temporal data across various fields.

New methods improve brain image data analysis using manifold learning techniques.

A new framework for creating reliable and accurate machine learning classifiers.

Examining how algorithms can protect privacy while optimizing decisions in personalized medicine.

This research tackles oversmoothing in graph convolutions to improve node classification accuracy.

A look into new methods for improving matrix denoising amidst complex noise.

A new approach to optimize Bayesian inference using generalized methods.