Modern computational tools let scientists explore huge numbers of possible molecules, materials and chemical reactions. But testing every combination in the lab is slow and costly. So how do ...

Bayesian model selection provides a coherent framework for comparing competing statistical models by balancing goodness of fit against model complexity through the use of prior distributions and ...

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 ...

Bayesian networks, also known as Bayes nets, belief networks, or decision networks, are a powerful tool for understanding and reasoning about complex systems under uncertainty. They are essentially ...