Researchers have employed Bayesian neural network approaches to evaluate the distributions of independent and cumulative ...

The FDA’s new draft guidance on Bayesian methodology signals a shift toward more flexible, data-driven clinical trial designs, enabling sponsors to use prior data and adaptive approaches to improve ...

Rainfall prediction has advanced rapidly with the adoption of machine learning, but most models remain optimized for overall ...

Researchers have developed a hybrid CFD-neural network model for predicting TAIs in hydrogen-fueled turbines, improving ...

The ROAR trial tested the hypothesis that returning familial hypercholesterolemia-associated genetic results leads to ...

In a remote corner of East Greenland, a section of mountain gave way, collapsing into a narrow glacial fjord bounded by steep ...

Advancements in Building Energy Modeling This year’s Building Simulation conference really dug into how we can make ...

New research from the University of St Andrews, the University of Copenhagen and Drexel University has developed AI ...

The representation of individual memories in a recurrent neural network can be efficiently differentiated using chaotic recurrent dynamics.

Discover four key identity and access priorities for the new year to strengthen your organization's identity security ...

Researchers at TU Wien are developing a model that interprets opinions not as diametrically opposed poles, but as overlapping ...