School of Power and Energy, Nanchang Hangkong University, Nanchang, China. China’s aviation industry, particularly its civil aviation sector, is undergoing rapid development, with the fleet of civil ...

Creating a highly accurate geological model at a large scale presents a considerable challenge, primarily due to constraints imposed by sparse data availability. A promising strategy to mitigate these ...

For a long time, filtered backprojection (FBP) has been the only reconstruction algorithm used in SPECT. However, it appears that the more widely available and increasingly fast iterative ...

Bayesian regression with linear basis function models. Introduction to Bayesian linear regression. Implementation with plain NumPy and scikit-learn. See also PyMC3 implementation. Gaussian processes.

In recent years, a learning method for classifiers using tensor networks (TNs) has attracted attention. When constructing a classification function for high-dimensional data using a basis function ...

TO THE EDITOR: Artificial intelligence (AI) systems, and computers in general, possess several advantages over humans. They have virtually perfect recall and are not subject to fatigue, mood ...

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: The convergence of expectation-maximization (EM)-based algorithms typically requires continuity of the likelihood function with respect to all the unknown parameters (optimization variables) ...

Adaptive Hierarchical Clustering is a dynamic method that flexibly organizes data into a hierarchy of clusters. Unlike traditional hierarchical clustering, it adaptively adjusts the number of clusters ...

If you use these materials for teaching or research, please use the following citation: Rhoads, S. A. (2023). pyEM: Expectation Maximization with MAP estimation in ...