Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, United States Department of Applied Mathematics, University of Washington, Seattle, United States Howard ...
A representation of the cause-effect mechanism is needed to enable artificial intelligence to represent how the world works. Bayesian Networks (BNs) have proven to be an effective and versatile tool ...
Abstract: Fitting overdispersed count data accurately and efficiently is instrumental for statistical modeling. Failing to capture the overdispersed nature of data ...
Abstract: Presence of code smells complicate the source code and can obstruct the development and functionality of the software project. As they represent improper behavior that might have an adverse ...
PyMC is a probabilistic programming library for Python that provides tools for constructing and fitting Bayesian models. It offers an intuitive, readable syntax that is close to the natural syntax ...
Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Hydrogen–deuterium exchange mass spectrometry (HDX/MS) is increasingly used to study ...
A full-code demo from Dr. James McCaffrey of Microsoft Research shows how to predict the type of a college course by analyzing grade counts for each type of course. General naive Bayes classification ...
EigenRand is a header-only library for Eigen, providing vectorized random number engines and vectorized random distribution generators. Since the classic Random functions of Eigen relies on an old C ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results