Statistics

A method for estimating the number of inmates over time and policy impacts.

Investigating the role of pre-trained models in energy management data challenges.

This article examines how personalized medicine uses omics data to improve survival outcomes for patients.

This article discusses methods to handle missing data in longitudinal studies.

Exploring the importance of considering variations in treatment effects.

New statistical approaches improve understanding of treatment effects on health outcomes.

A new method enhances understanding of risk through past outcomes in studies.

This study analyzes commuting changes in Atlanta during COVID-19.

RESI streamlines the reporting of effect sizes in research studies.

A focused approach to improving variational inference accuracy.

This study highlights methods for analyzing brain signals using covariance matrices.

Examining structures in data through connected clustering methods.

RNNC offers efficient analysis of satellite data, improving accuracy and speed.

A guide to spatio-temporal point processes and their applications across various fields.

CUSP priors improve Bayesian factor analysis by managing model complexity.

New sampling techniques enhance accuracy and efficiency in analyzing complex hidden systems.

A new model enhances how data is generated by understanding causal factors.

Examining the challenges and solutions to bias in face generation technology.

Diffusion models transform how images and media are created using data patterns.

A method to enhance fairness in link prediction within GNNs.

A new VAE model enhances synthetic data creation while ensuring privacy.

Explore Normalizing Flows and their impact on complex data analysis.

A fresh approach helps identify discrimination in automated decision-making systems.

A look at data processing methods for improving predictive model outcomes.

A look at stepped wedge trials and their significance in research.

Research on Arctic warming and its effects on sea ice and climate.

A structured approach to improve causal inference accuracy in observational studies.

RESI streamlines the reporting of effect sizes in research studies.

A look at data processing methods for improving predictive model outcomes.

Strategies to control false discoveries enhance the reliability of scientific findings.

A focused approach to improving variational inference accuracy.

A deep dive into model confidence sets and variable selection in statistics.

Examining the reliability and validation of influence functions in deep learning models.

A new algorithm enhances accuracy in forecasting disease outbreaks through detailed data generation.

A discussion on merging statistical approaches for better data analysis.

A fresh approach uncovers individual variations in program treatment effects.

Methods to accurately calculate averages and variances despite missing data points.

A method for predicting specific outcomes using relevant past data.

A new framework for better statistical inference in research and analysis.

A fresh approach improves signal detection in noisy environments with limited data.

A look at how Policy Mirror Descent enhances decision-making in MDPs.

A new algorithm for estimating transformations amid data errors.

A deep dive into model confidence sets and variable selection in statistics.

Techniques to identify important features in complex datasets are essential.

Integrating L2O transformations and graphical models improves parameter estimation in SEMs.

Lasso helps identify important data in complex datasets.

Analyzing relationships between groups of random variables for better insights.

This article discusses renewed interest in fiducial inference using generalized methods.