Latest Articles for Statistical Methods

A method for identifying regimes in complex data models.

Learn how step size affects gradient descent in logistic regression.

Examining methods to analyze jets from high-energy particle collisions.

Learn how importance weighting enhances model performance amid covariate shifts.

Examining better methods to analyze health treatment trials.

Introducing a new method for Bayesian neural networks that improves uncertainty modeling.

A new approach enhances the accuracy of language model evaluations.

This study evaluates survival analysis techniques using simple datasets with missing data.

A method to identify data shifts without labels.

A new approach to optimization allows better analysis of diverse step sizes.

Examining the challenges of parsimony for understanding species relationships.

Key insights on how to select topics in text analysis.

New method improves efficiency in comparing complex data sets.

A new methodology improves treatment evaluation for personalized medicine.

This research discusses federated learning's role in protecting privacy during data analysis.

This research improves machine learning model reliability via calibration and recalibration techniques.

New approaches propose better handling of ties in rankings across various fields.

A study on using Variational Bayes for spatial models with missing values.

A study on cognitive biases affecting quality evaluations in crowdsourced tasks.

Bayesian emulators enhance decision-making in petroleum well control under uncertainty.

A new method improves parameter estimation in quantum systems.

A new framework enhances hypothesis testing in additive regression models.

Research reveals how AI can learn causal reasoning from examples.

Explore a simple method for identifying shifts in factor models using residuals.

Learn how Bregman divergence aids in measuring data differences and improving machine learning models.

A detailed analysis of ODI cricket's performance trends over 36 years.

Using Bayesian methods to improve treatment effect estimates in medical research.

A new method to enhance donor selection for causal effect estimation.

CLAMS automates clustering model selection for datasets lacking labels.

This paper presents the Gamma Variance Model for accurate particle mass measurements.

A fresh approach to understand causal effects in treatment studies with continuous variables.

A systematic approach to finding the best models for dark energy using supernova data.

New filtering methods improve climate predictions and decision-making.

Bayesian methods improve data analysis speed and accuracy for large datasets.

A new method merges Bayesian inference and machine learning for better data analysis.

Explore how the stochastic block model helps identify communities in networks.

KnewImp improves accuracy in missing data imputation and simplifies training processes.

This article explores a new approach to assess treatment impact considering changing factors.

This article discusses how Bayesian methods improve confidence in neural network predictions.

A closer look at disclosure risks in synthetic data and privacy protection.