Probabilistic programming allows for automatic Bayesian inference on user-defined probabilistic models.Recent advances Tortilla Servers in Markov chain Monte Carlo (MCMC) sampling allow inference on increasingly complex models.This class of MCMC, known as Hamiltonian Monte Carlo, requires gradient information which is often not readily available.Py
Objective: Acute myocardial infarction (AMI) is the main cause of cardiovascular events worldwide.AMI commonly occurs in elderly patients because of atherosclerotic process related to common risk factors.Consequently, the rupture of atheromatous plaque with deleterious sequela is the common etiology of the disease.However, there are less studied et
Monitor mode packet capturing of WLAN is used to derive Access points and devices in the range for localization or occupancy purposes.The general modality of capturing and analysis in almost all available studies is to capture packets by being static (STT) at a location and indoors.In STT mode, the beacon and probe packets extract insights about th