Discover how multivariate models use multiple variables for investment forecasting, risk analysis, and decision-making in finance. Ideal for portfolio management.

Background Up to half of patients with infective endocarditis (IE) require cardiac surgery. Although anaemia is common, its precise prevalence, transfusion practices and impact on outcomes in ...

Objective This study aimed to evaluate the prevalence and predictors of cardiovascular disease (CVD), chronic kidney disease ...

The joint probability of two or more variables being “extreme” is relevant in Flood and Coastal Risk Management (FCRM) in various contexts, including: Assessing the likelihood of extreme peak flow ...

Abstract: Variable Subset Forecasting (VSF) presents a critical challenge where variable availability fluctuates between the training and inference stages. This paper introduces a novel solution to ...

Objectives In patients with chronic obstructive pulmonary disease (COPD), severe exacerbations (ECOPDs) impose significant morbidity and mortality. Current guidelines emphasise using ECOPD history to ...

Researchers have proposed a unifying mathematical framework that helps explain why many successful multimodal AI systems work ...

This study provides important evidence that negative affect is associated with slower cognitive processing in daily life, with findings replicated across three independent samples and supported by ...

Sea foams are caused by algal blooms and can represent large areas in coastal waters during ocean fronts associated with ...

Abstract: Anomaly detection in multivariate time series (MTS) plays a crucial role in various domains, particularly in multimedia. While significant progress has been made in modeling normal data ...

Can you chip in? As an independent nonprofit, the Internet Archive is fighting for universal access to quality information. We build and maintain all our own systems, but we don’t charge for access, ...