Statistics

A new method improves estimates by using negative controls to combat hidden biases.

This work discusses synthetic data generation using differential privacy for economic studies.

Research highlights the importance of PSA monitoring for salvage therapy in prostate cancer.

Investigating neural connections through bi-clustering methods.

A comprehensive study on rainfall impacts in Southern India's Western Ghats over a century.

A study on measuring escalator energy use for better maintenance practices.

A new model estimates total infections using mobility data and demographic factors.

New neural network method improves roughness estimation in SAR images.

A new model enhances gene interaction studies using auxiliary variables.

Learn how to avoid biases in model selection.

A new method enhances efficiency in complex data analysis using weighted Riesz particles.

Exploring new methods for reliable heart disease data analysis.

A study on enhancing drug prediction models for better cancer therapies.

MELAGE helps doctors and researchers analyze brain images for better diagnosis.

This study enhances spectroscopy methods for better dairy product analysis.

A new method for clustering large datasets effectively and efficiently.

A new method for effectively representing and manipulating sparse graphs.

A new method enhances deep learning models on FPGAs for faster processing.

Discover how robust machine learning models handle varying data sources for better predictions.

A method for accurate data estimation using device collaboration.

A look at how factors influence one another over time.

BETULA enhances hierarchical clustering, making it faster and more efficient.

This article discusses using diffusion models with discrete data through the probability simplex.

Introducing COPS, a method for efficient deep learning model training with less data.

A framework for measuring and improving fairness in AI systems.

New spectral approach enhances multivariate Matérn models for spatial data analysis.

Discover how robust machine learning models handle varying data sources for better predictions.

A new method improves estimates by using negative controls to combat hidden biases.

A closer look at causality and its measurement in observational research.

Bayesian methods are reshaping how clinical trials incorporate past data for better decisions.

A closer look at effect size in student performance analysis.

A look at how factors influence one another over time.

New spectral approach enhances multivariate Matérn models for spatial data analysis.

Explore different methods in causal modeling and their significance for research.

Exploring geometric perspectives on correlation matrices for deeper insights.

This article presents a new method for selecting radius in complex data analysis.

Understanding the complexities and solutions in geospatial data analysis.

Examining how parts interact to create new outcomes in complex systems.

PORTSEA advances extreme value statistics, influencing various fields and education.

This article examines how gamification boosts student engagement in flipped classrooms.

New spectral approach enhances multivariate Matérn models for spatial data analysis.

Learn how Bayesian methods enhance prediction accuracy in uncertain outcomes.

A study on identifying the best option while ensuring data privacy.

Learn how robust tensor decomposition improves data analysis amidst noise and outliers.

This article examines power variations in stochastic processes influenced by fractional Brownian motion.

Learn how machine learning models perform on unseen data.

Exploring the impact of local discrepancy and functions on QMC techniques.

A new method enhances prediction reliability despite incorrect data labeling.