Concr CEO Irina Babina and CTO Matthew Griffiths unpack how Bayesian foundation models can excel at uncertainty management to ...

Longitudinal data analysis is an essential statistical approach for studying phenomena observed repeatedly over time, allowing researchers to explore both within-subject and between-subject variations ...

Google Research has proposed a training method that teaches large language models to approximate Bayesian reasoning by learning from the predictions of an optimal Bayesian system. The approach focuses ...

As rare disease trials face persistent feasibility challenges, Bayesian designs are gaining momentum by enabling more flexible, data-driven approaches that integrate prior knowledge, reduce sample ...

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, ...

In this video interview, David Morton, PhD, director of biostatistics at Certara, explains how regulatory momentum is ...

Artificial intelligence can solve problems at remarkable speed, but it's the people developing the algorithms who are truly driving discovery. At The University of Texas at Arlington, data scientists ...

Dr. James McCaffrey of Microsoft Research shows how to predict a person's sex based on their job type, eye color and country of residence. Naive Bayes classification is a classical machine learning ...