Zach Cox is a software engineer at Charles River Analytics, Inc. Cambridge, Mass.-based company that for the past 20 years has built intelligence and decision support applications for military, ...

For making probabilistic inferences, a graph is worth a thousand words. A Bayesian network is a graph in which nodes represent entities such as molecules or genes. Nodes that interact are connected by ...

Trolling the universe this morning, Richard Cohen wrote a column arguing that it wasn’t racist of George Zimmerman to suspect Trayvon Martin of being a criminal because everyone knows that a ...

A new technical paper titled “Bringing uncertainty quantification to the extreme-edge with memristor-based Bayesian neural networks” was published by researchers at Université Grenoble Alpes, CEA, ...

How does one model a simple cell-signaling pathway? Consider a simple example consisting of a stimulant, an extracellular signal, an inhibitor of the signal, a G protein–coupled receptor, a G protein ...

Bayesian networks are particularly useful for dealing with high dimensional statistical problems. They allow a reduction in the complexity of the phenomenon under study by representing joint ...