Independent of its path-breaking, field-founding merits, the book presents a beautifully crafted combination of descriptive probabilistic choice models with discrete social choice strategies supported ...

A group of scientists has just proposed a brand new equation aiming to figure out the probability of intelligent life ...

Probabilistic models, such as hidden Markov models or Bayesian networks, are commonly used to model biological data. Much of their popularity can be attributed to the existence of efficient and ...

Researchers have developed a deep learning-based approach that significantly streamlines the accurate identification and ...

Probabilistic graphical models are a powerful technique for handling uncertainty in machine learning. The course will cover how probability distributions can be represented in graphical models, how ...

Behavioral Social Choice looks at the probabilistic foundations of collective decision ... of cycles as a function of sample size and insights into how alternative model specifications can change our ...