Statistics

Innovative methods to retrieve time labels from noisy dynamical data.

A look at record linkage algorithms and their impact on data analysis.

Examining patient survival with polyhazard models enhances data accuracy and treatment decisions.

New filtering methods improve climate predictions and decision-making.

Bayesian neural networks enhance material behavior predictions with uncertainty estimates.

A study of temperature changes in Spain and Portugal over the past century.

A novel approach to understanding stock interactions during market changes.

This article discusses how knowledge graphs improve feature selection in data analysis.

A novel approach to understanding stock interactions during market changes.

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

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

A new method for estimating conditional expectations efficiently in uncertain environments.

Examining how population models shape genealogies and influence genetic algorithms.

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.

New attention methods improve transformer models in efficiency and performance.

Elliptical Attention improves focus and performance in AI tasks.

RPC-Attention enhances self-attention models for better performance on noisy data.

A new method that combines strengths of Sliced and Tree Wasserstein for dynamic data analysis.

Calibration ensures predictions align with actual outcomes across various fields.

Learn how in-context learning improves predictive models using multiple data sets.

Exploring the value of approximately equivariant models in machine learning.

This article introduces minimax quantiles for better statistical estimates.

Innovative methods to retrieve time labels from noisy dynamical data.

A method to identify causal impacts in training programs and interventions.

A look at record linkage algorithms and their impact on data analysis.

Researchers introduce a method to evaluate independence of random variables using quantiles.

Examining patient survival with polyhazard models enhances data accuracy and treatment decisions.

This study examines Bayesian PINNs for estimating PDE parameters from noisy data.

Exploring new techniques in experimental design and data analysis for scientific research.

Simplifying spatial data analysis with directed graphical models for yes/no outcomes.

This research develops methods for fair resource allocation despite limited user feedback.

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.

Innovative methods to retrieve time labels from noisy dynamical data.

This article introduces minimax quantiles for better statistical estimates.

This study examines Bayesian PINNs for estimating PDE parameters from noisy data.

Two new estimators enhance accuracy in analyzing item response data.

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

Learn how to identify unusual patterns in time-series data with Markov depth.

Learn techniques for estimating missing values in stationary stochastic sequences.

A two-stage testing approach simplifies interactions among numerous genetic variables.