Most chatter about AI in other than research and academic institutions is about Machine Learning (ML) and various forms of neural nets and deep learning. Natural Language (speech recognition, language ...

In my practice, I find most people involved with advanced analytics, such as predictive, data science, and ML, are familiar with the name Bayes, and can even reproduce the simple theorem below. Still, ...

Answer any query from a joint distribution. Construct joint distribution from conditional probability tables using chain rule. Construct joint distribution from Bayes net and conditional probability ...

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 ...

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 ...

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...

A collaboration including the University of Oxford, University of British Columbia, Intel, New York University, CERN, and the National Energy Research Scientific Computing Center is working to make it ...

Abstract: Efficient second-order probabilistic inference in uncertain Bayesian networks was recently introduced. However, such second -order inference methods presume training over complete training ...

Operational risk is an important quantitative topic as a result of the Basel II regulatory requirements. Operational risk models need to incorporate internal and external loss data observations in ...