The iQRM Warm-Ups are short, half hour sessions that review the basics covered in iQRM. This is a tour of the foundational math without application. The seminar covers probability, the normal ...

Abstract: A quantum generalized divergence by definition satisfies the data-processing inequality; as such, the relative decrease in such a divergence under the action of a quantum channel is at most ...

Abstract: We consider a non-Bayesian estimation problem preceded by a detection step. In this framework, the observation model follows one of two hypotheses: an informative hypothesis, where the data ...

Provides a one-semester course in probability and statistics with applications in the engineering sciences. Probability of events, discrete and continuous random variables cumulative distribution, ...

A semi-parametric generalization of the proportional hazards regression model is defined, whereby the hazard functions can cross for different values of the covariates. In the two-sample comparison, ...

FALL 2025: Monday 2:00-3:00 PM, Tuesday 11:00 AM-12:00 PM, Wednesday 2:00-3:00 PM, Thursday 11:00 AM-12:00 PM, other times by chance or by appointment Paul M. Sommers is the Paige-Wright Professor of ...

Recent advances in high-throughput microbiome profiling have generated expansive data sets that offer unprecedented ...

James is a published author with multiple pop-history and science books to his name. He specializes in history, space, ...

This paper presents important new findings about the impact of the TAK-003 vaccine against dengue based on a convincing reanalysis of trial data. The results corroborate those of the original trial ...

AB-1005, a glial cell line-derived neurotrophic factor (GDNF) investigational gene therapy, is being evaluated for the treatment of moderate-stage Parkinson’s disease in the REGENERATE-PD trial ...

Objective Handball is a popular team sport with injury risks, especially to the shoulder. This systematic review aims to ...

Understanding the neural mechanisms underlying associative threat learning is essential for advancing behavioral models of threat and adaptation. We investigated distinct activation patterns across ...