Statistics

A novel method enhances tissue image analysis for better disease diagnosis.

A look at new techniques for identifying cause-and-effect in various fields.

A look at Particle Swarm Optimization and its applications in various fields.

Using data analysis to predict Australian Rules Football game results.

A new method improves wind predictions using statistical models and data integration.

Machine learning models like FourCastNet enhance weather forecasting accuracy through data assimilation.

Examining how stochastic models help in predicting infectious disease spread.

A new watermarking method aids in identifying synthetic tabular data.

A novel technique generates samples efficiently from unknown probability distributions using limited data.

A look at Particle Swarm Optimization and its applications in various fields.

New methods improve speed and efficiency in solving time-dependent equations.

A method combining SGD and privacy techniques for effective data analysis.

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 methods enhance fNIRS analysis using synthetic data and machine learning.

This paper discusses enhancing learning from flawed human feedback in recommendation systems.

A new MCMC method improves efficiency in complex data analysis.

Learn how Collaborative Trees can clarify variable interactions in data analysis.

A study revealing factors that influence in-context learning in Transformers.

Exploring Local SGD's strengths and weaknesses in diverse data environments.

A new method improves treatment effect estimates in complex datasets.

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

A new method to analyze relationships between two variables using spline approximations.

Learn how Collaborative Trees can clarify variable interactions in data analysis.

A look into using Distributed Tensor PCA for effective data analysis across locations.

Examining how interventions affect individuals through cluster and network interference.

Introducing a non-parametric Box-Cox model for better analysis of high-dimensional data.

This article reviews the methods and importance of Comparative Judgement in assessments.

A novel method enhances the testing of causal discovery algorithms.

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

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.

A look into using Distributed Tensor PCA for effective data analysis across locations.

A look at PCR's role in analyzing high-dimensional datasets.

A versatile tool for analyzing diverse data distributions in statistics.

A method combining SGD and privacy techniques for effective data analysis.

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.