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 robust ...

Abstract: Feature weighting is used to alleviate the conditional independence assumption of Naïive Bayes text classifiers and consequently improve their generalization performance. Most traditional ...

Dr. Bayes's research and teaching interests center on the political behavior and political psychology of everyday Americans, and particularly, how they process scientific information in order to form ...

Abstract: This paper proposes a direct model for conditional probability density forecasting of residential loads, based on a deep mixture network. Probabilistic residential load forecasting can ...