Statistics

Seamless design aims to speed up cancer treatment development.

A new method improves understanding of treatment effects by merging RCT and observational data.

A new method improves accuracy in predicting state transitions using Markov chains.

Researchers use NN-CDFs to study neutrino sources more effectively.

A new method enhances outcome selection in observational studies to minimize biases.

Research reveals the oral microbiome's impact on health and disease.

A fresh method for analyzing historical foehn wind occurrences using data analysis.

A new approach combining generative modeling and boosting for better learning outcomes.

Learn how Bayesian online learning adapts models with incoming data.

A new model enhances the analysis of complex health data.

New tools improve efficiency using lower precision in computations for research.

Examining methods to analyze jets from high-energy particle collisions.

Research highlights the importance of biomarkers in detecting Alzheimer's disease early.

New method improves efficiency in comparing complex data sets.

A new framework enhances hypothesis testing in additive regression models.

A look at key data pipeline tools and their roles in data engineering.

An overview of decision-making under uncertainty with the streaming model.

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

Learn how Bayesian online learning adapts models with incoming data.

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

New algorithm achieves low regret in dynamic learning environments without prior knowledge.

Introducing a novel approach to identify hidden factors in biological data.

Discussing long-term fairness in technology and its social impact.

New methods improve molecular design by measuring prediction uncertainty.

Seamless design aims to speed up cancer treatment development.

A new method improves understanding of treatment effects by merging RCT and observational data.

This article discusses methods for identifying causal links in linear non-Gaussian models.

New methods improve accuracy and efficiency in simulations using varying fidelity levels.

A new factor model improves data analysis over time.

A novel method enhances the accuracy of treatment effect estimates over time.

A new method improves accuracy in predicting state transitions using Markov chains.

A new model enhances prediction accuracy for treatment effects over time.

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.

A new factor model improves data analysis over time.

A look at nonparametric regression methods using geometric graphs and Bayesian approaches.

This study focuses on OTA computing to improve device communication in networks.

Exploring causal spaces and their implications for understanding systems and interactions.

Examining vulnerabilities from clean-label backdoor attacks and how generalization bounds can help.

Random matrices unlock new approaches for solving complex problems in various fields.

A new method enhances outcome selection in observational studies to minimize biases.

This article discusses adaptive MCMC methods and their applications in complex distributions.