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 ...

This GEN Spotlight on RNA Therapeutics brings you three interlinked sessions that feature outstanding researchers exploring various aspects of RNA biology and therapeutics.

Quantum computing news usually picks up near the end of the year, as companies try to provide evidence that they are hitting ...

Los Angeles -- Richard E. Carson, PhD, has been named the 2026 recipient of the prestigious Paul C. Aebersold Award. Carson is professor of Biomedical Engineering and of Radiology and Biomedical ...

Abstract: Wideband source localization using acoustic sensor networks has been drawing a lot of research interest recently. The maximum-likelihood is the predominant objective which leads to a variety ...

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 ...

This paper shows that the Expectation-Maximization (EM) algorithm for regime-switching dynamic factor models provides satisfactory performance relative to other estimation methods and delivers a good ...

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 ...

In this paper, we consider the construction of the approximate profile-likelihood confidence intervals for parameters of the 2-parameter Weibull distribution based on small type-2 censored samples. In ...