Statistics

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

A new method enhances predictions for cancer patients using image and gene data.

Scientists use machine learning to improve predictions in cancer drug combinations.

A structured approach to finding meaningful spatial relationships in diverse fields.

This study examines statins and cognitive ability, considering patient death in outcomes.

Proper scoring rules enhance the evaluation of probabilistic forecasts across various fields.

A look into identifying regional-colocation patterns and minimizing false discoveries.

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

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.

A look at the benefits of expectation propagation for statistical analysis.

Exploring how noisy data affects model performance on unseen data.

Learn how reduced-order models aid in analyzing complex systems using causation entropy.

This method enhances prompt creation for large language models, improving overall performance.

Scientists use machine learning to improve predictions in cancer drug combinations.

AnInfoNCE improves contrastive learning by addressing challenges in data augmentation.

A study on balancing transfer learning and individual privacy in data usage.

Innovative methods to analyze extreme values in weather and environmental data.

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

A look at how DIVE enhances understanding of treatment effects across populations.

Simplified methods for determining sample sizes in Bayes factor studies.

A study on balancing transfer learning and individual privacy in data usage.

Innovative methods to analyze extreme values in weather and environmental data.

A clear look at VARMA models and their applications in time series data.

Combining AI and medical knowledge improves treatment strategies in precision medicine.

A look at models for related survival times and competing risks.

This paper discusses the Poisson mechanism for maintaining privacy in data synthesis.

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.

A look at how transformations impact mean and covariance in data analysis.

A study on balancing transfer learning and individual privacy in data usage.

Innovative methods to analyze extreme values in weather and environmental data.

BART is a powerful tool for predicting outcomes in various fields.

A look at models for related survival times and competing risks.

Two innovative methods offer insights into system aging and reliability.

Proper scoring rules enhance the evaluation of probabilistic forecasts across various fields.

NCP simplifies learning conditional probabilities for better decision-making across fields.