Researchers developed purNPE, a simulation-based Bayesian deep-learning framework that enables uncertainty-aware tumor ...

A new Bayesian framework called PIML combines machine learning analysis of electrical impedance signals with clinical prior ...

Researchers at The University of Texas at Arlington have developed a new computational tool that helps scientists pinpoint proteins known as transcriptional regulators that control how genes turn on ...

Good evening, everyone! It is time once again to bring you the latest from the front lines of data science and AI. Tonight, ...

When a computer scientist publishes genetics papers, you might think it would raise colleagues’ eyebrows. But Daphne Koller’s research using a once obscure branch of probability theory called Bayesian ...

In the ever-evolving toolkit of statistical analysis techniques, Bayesian statistics has emerged as a popular and powerful methodology for making decisions from data in the applied sciences. Bayesian ...