Latest Articles for Statistical Modeling

New algorithms enhance feature selection speed and accuracy in statistical models.

This paper discusses new insights in causal regression for better decision-making.

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

Study evaluates fairness of COVID-19 case predictions across racial groups.

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

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

New normalization methods improve spatial data predictions and analysis efficiency.

Introducing Deep Double Poisson Networks for better discrete predictions.

A look at methods for estimating extreme values in bivariate normal data.

Study analyzes generalization and performance of random feature ridge regression using eigenvalues.

This article presents a method to reduce computational costs in estimating unknown quantities.

Researchers develop a fast emulator for complex computer models.

A new approach in federated learning captures data dependencies while ensuring privacy.

CASBAH improves the study of treatment effects using continuous post-treatment variables.

A new modular approach enhances variational inference in probabilistic programming languages.

New methods boost accuracy in handling missing data for staged trees.

Hierarchical Bayesian modeling offers a path to more accurate gravitational wave insights.

Strategies to improve predictive accuracy in statistical modeling through better SNR management.

This article explores the relationship between NMF and LDA in data analysis.

A new method enhances speed and accuracy in logistic regression predictions.

Mutual learning boosts performance and uncertainty estimation in Bayesian Neural Networks.

Introducing a new method for statistical modeling on quantum processors.

A look into spatio-temporal models and their applications across various fields.

A new solution to enhance data analysis through outlier management.

This study examines variational inference using fixed-variance Gaussian mixtures.

Innovative approach to create effective acquisition functions for Bayesian optimization.

New algorithms improve understanding of variable relationships in causal discovery.

Exploring the role of generalized metric subregularity in enhancing numerical optimization techniques.

An overview of using the Categorical Compact Genetic Algorithm for better optimization.

A deep dive into how uncertainty impacts predictions in hierarchical modeling.

A new framework enhances time series data for energy systems.

Introducing a new method for sampling from complex probability distributions in Bayesian inference.

DistPred improves outcome predictions by accounting for uncertainty effectively.

New methods improve material property inference in mechanics and medical imaging.

Exploring conditional mean estimation in quantized signal systems and its applications.

A novel approach to understanding stock interactions during market changes.

A method to enhance community detection in complex networks by classifying nodes.

An overview of two-way clustering methods for better statistical results.

A method for effective analysis of high-dimensional tensor factor models in finance.

Study reveals how muscle activation affects mouse locomotion on a treadmill.