Statistics

This study uses LiDAR to improve forest biomass estimates in Alaska's Tanana Inventory Unit.

A novel approach improves detection of faint galaxies linked to dark matter.

A statistical model helps forecast dengue outbreaks using climatic and geographical data.

Study reveals how diabetic neuropathy affects nerve fibers in the skin.

A new framework enhances decision-making for evaluating treatments in clinical trials.

This article discusses ensemble-based methods for improving ocean predictions amidst sparse data.

This article explains how RD designs inform medical treatment effects using cutoff scores.

A system to analyze human and animal sounds in large audio datasets.

Introducing mGHS for effective network analysis across diverse datasets.

Research reveals a new approach to analyze health outcomes over time.

This article examines the trade-offs in factorized approximations used in variational inference.

SNAMs offer clearer insights into machine learning predictions.

A new method improves data classification using covariance matrix clustering.

Learn about key concepts in optimization and sampling for effective decision-making.

Discover innovative methods for analyzing longitudinal data using the lqmix R package.

RESI streamlines the reporting of effect sizes in research studies.

This article examines how algorithms can adjust to shifts in user preferences.

A new method for creating prediction sets in federated learning while ensuring privacy.

HoroSVM offers improved classification for hierarchical data using horospheres.

New methods aim to improve analysis of high-dimensional data using statistical techniques.

RCIG enhances dataset distillation, improving efficiency and accuracy in machine learning.

New methods improve predictions using Kernel Ridge Regression in education and other fields.

GFlowNet-EM enhances learning from data with hidden variables using innovative sampling methods.

An overview of PAC learning concepts and their practical implications in machine learning.

Learn how selection bias impacts research and how to analyze it effectively.

Introducing mGHS for effective network analysis across diverse datasets.

Investigating fair decision-making systems through causal relationships and individual responses.

Introducing techniques to improve estimation in periodic autoregressive models affected by noise.

Research reveals a new approach to analyze health outcomes over time.

A look at how multiway PCA improves analysis of complex datasets.

This article explains how RD designs inform medical treatment effects using cutoff scores.

A new method improves understanding of how mixed chemical exposures impact health outcomes.

New sampling methods improve efficiency and accuracy in Bayesian Neural Networks.

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.

Learn how trimmed means improve estimates in data analysis.

New methods aim to improve analysis of high-dimensional data using statistical techniques.

New methods improve predictions using Kernel Ridge Regression in education and other fields.

Introducing techniques to improve estimation in periodic autoregressive models affected by noise.

A look at how multiway PCA improves analysis of complex datasets.

A look into sparse Bayesian inference and its role in recovering true signals.

A new method combines tensors and interpolation for better system identification.

Learn how prediction sets help manage uncertainty in changing environments.