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: To estimate time-varying MIMO channel at base station, traditional downlink (DL) channel restoration schemes usually require the reconstruction for the covariance of downlink process noise ...

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 ...

Abstract: In this paper, the novel extended space-alternating generalized expectation-maximization (SAGE) algorithm, providing joint propagation channel multi-path component (MPC) estimation and ...

SCAPE is a tool for estimating alternative polyadenylation (APA) events from single-end or pair-end scRNA-seq data (10x, Microwell-seq). The scRNA-seq must be generated by protocols based on polyT ...

Manipulation of deformable objects has given rise to an important set of open problems in the field of robotics. Application areas include robotic surgery, household robotics, manufacturing, logistics ...

Filtered backprojection (FBP) algorithms reduce image noise by smoothing the image. Iterative algorithms reduce image noise by noise weighting and regularization. It is believed that iterative ...

Mathematical modeling and analysis of biochemical reaction networks are key routines in computational systems biology and biophysics; however, it remains difficult to choose the most valid model. Here ...

Images of the inside of the human body can be obtained noninvasively using tomographic acquisition and processing techniques. In particular, these techniques are commonly used to obtain images of a ...