Statistics

A look at how GPS data enhances traffic flow mapping accuracy.

A new framework helps researchers align and analyze neuron activity data for memory studies.

A fresh approach to ranking data using Bayesian models to group similar items.

A look at using historical data to enhance clinical trial analysis.

Discover how mixture priors can enhance analysis of replication studies.

New models reveal complex recovery patterns of coral reefs after disturbances.

This article examines how credit ratings affect a company's leverage decisions.

This article discusses a new method for calibrating agent-based models using random forests.

New techniques in sampling improve efficiency in statistical analysis.

A novel technique using electrostatics for better data sampling and estimation.

New approaches to tackle complex linear systems efficiently.

A new method for tuning hyperparameters using Bayesian ideas.

The FLAP method enhances forecasting by using existing data in new ways.

A novel approach to study time series data and its factors in healthcare.

Efficient modeling techniques enhance engineering design processes and reduce costs.

A new method significantly speeds up sampling from non-Gaussian Lévy processes.

Exploring the role of tensor networks in enhancing quantum machine learning.

Exploring how DNNs recover functions in overparameterized settings.

Improving reinforcement learning with value function estimates for faster task adaptation.

New methods reduce communication costs for faster data science computations.

Exploring new methods for better decision-making under uncertainty in AI systems.

A look into randomized smoothing as a defense for machine learning models.

Examining the role of robustness in estimating unknown distributions from samples.

New methods using diffusion models enhance cybersecurity against adversarial examples.

New models provide insight into complex systems by focusing on individual components.

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

A novel approach to enhance predictions of air quality using satellite data.

A look into how PDA helps analyze complex functional data.

CHCDS improves prediction accuracy without data partitioning.

A new framework improves prediction accuracy while minimizing the size of prediction sets.

Standardizing criteria can enhance AI tools for detecting basal cell carcinoma.

Study examines how brain images reveal insights into primary progressive aphasia.

A look into how the estimand framework improves clinical trial analysis.

A fresh approach to understanding complex human connections through fuzzy social network analysis.

A study on how Park-and-Ride can reduce congestion and emissions.

Information significantly impacts decision-making processes across various fields.

Benford's Law reveals odd patterns in first digits across data sets.

A method for detailed signal analysis over time and frequency.

New methods enhance understanding of the universe through weak gravitational lensing data.

A study on how information travels through social networks with community structures.

Examining the role of robustness in estimating unknown distributions from samples.

Exploring the role of structured tensor priors in improving data estimates.

Discover the basics of learning Dynamic Bayesian Networks from data.

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

CHCDS improves prediction accuracy without data partitioning.

This article examines the significance of maxima and the spacing test in Gaussian random fields.

A look into how eigenmaps improve data analysis through effective scaling.

A new method boosts generative models' performance even with scarce training data.