DynIMTS replaces static graphs with instance-attention that updates edge weights on the fly, delivering SOTA imputation and P12 classification ...

Professor Klaus Nordhausen develops modern multivariate statistical methods to analyze high-dimensional and large datasets in different fields.

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

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

The GC–MS dataset was integrated with the sensory data using a series of exploratory and predictive multivariate statistical ...

By modeling the single-trial electroencephalogram of participants performing perceptual decisions, and building on predictions from two century-old psychological laws, we estimate the times of ...

A research team introduces a fully automated, non-destructive phenotyping platform that combines X-ray fluorescence ...

Background The relationship of social determinants of health (SDOH), environmental exposures and medical history to lung function trajectories is underexplored. A better understanding of these ...

Discover why surface chemistry matters and how XPS imaging modes enable deeper insight into materials performance.

Delayed onset of canonical babbling and first words is often reported in infants later diagnosed with autism spectrum disorder (ASD). Identifying the neural mechanisms underlying language acquisition ...

In patients with high PD-L1 expression identified before surgery, clinicians should consider the possibility of lymph node metastasis when determining surgical strategy, including the extent of lymph ...

Major hurdles in early-stage drug discovery include how to triage hit compounds identified from cell-based screens, as well as how to rapidly evaluate their cellular efficacy and pinpoint side effects ...