In this paper we propose a Monte Carlo maximum likelihood estimation strategy for discretely observed Wright–Fisher diffusions. Our approach provides an unbiased estimator of the likelihood function and is based on exact simulation techniques that are of s ...
Background Superimposition of farfield (FF) and nearfield (NF) bipolar voltage electrograms (BVE) complicates the confirmation of pulmonary vein (PV) isolation after catheter ablation of atrial fibrillation. Our aim was to develop an automatic algorithm ba ...
Sedentary lifestyle is currently considered a global pandemic, associated with major health problems such as cardiovascular disease and premature death. Regular physical activity (PA) is one way to address this problem, as it brings a variety of health ben ...
We present a framework for performing regression when both covariate and response are probability distributions on a compact and convex subset of Rd. Our regression model is based on the theory of optimal transport and links the conditional Fr'echet m ...
Cybersickness still poses a significant challenge to the widespread usage of virtual reality (VR), leading to different levels of discomfort and potentially breaking the immersive experience. Researchers have attempted to discover the possible fundamental ...
Point clouds are effective data structures for the rep- resentation of three-dimensional media and hence adopted in a wide range of practical applications. In many cases, the portrayed data is expected to be visualized by humans. After acquisition, point c ...
Vagus nerve stimulation (VNS) is an FDA-approved technique for the neuromodulation of the autonomic nervous system. There are many therapeutic applications where VNS could be used as a therapy, such as cardiovascular diseases, epilepsy, depression, and inf ...
The aim of this paper is to introduce a new mathematical model that simulates myocardial blood perfusion that accounts for multiscale and multiphysics features. Our model incorporates cardiac electrophysiology, active and passive mechanics, hemodynamics, v ...
Functional data are typically modeled as sample paths of smooth stochastic processes in order to mitigate the fact that they are often observed discretely and noisily, occasionally irregularly and sparsely. The smoothness assumption is imposed to allow for ...
