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 ...

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 ...

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 ...

In this paper, I construct players' prior beliefs and show that these prior beliefs lead the players to learn to play an approximate Nash equilibrium uniformly in any infinitely repeated slightly ...

The Bayesian Learning Consortium is an industry-sponsored research consortium focusing on advanced quantitative methods for subsurface characterization. The goal of the consortium is to develop ...