A method is presented for the analysis of dynamic positron emission tomography (PET) data using sparse Bayesian learning. Parameters are estimated in a compartmental framework usin...
Jyh-Ying Peng, John A. D. Aston, R. N. Gunn, Cheng...
With the goal to generate more scalable algorithms with higher efficiency and fewer open parameters, reinforcement learning (RL) has recently moved towards combining classical tec...
Background: Dynamic modeling of metabolic reaction networks under in vivo conditions is a crucial step in order to obtain a better understanding of the (dis)functioning of living ...
I. Emrah Nikerel, Wouter A. van Winden, Walter M. ...
Today, a wide range of 802.11-based Wireless LANs (WLANs) have become dominant to provide wireless Internet access for file transfers. For engineering purposes, there is a need fo...
In the first part of the paper, daily price data for the past three summer seasons in the PJM wholesale market are used to estimate a stochastic regime switching model. These data...