Abstract: State of charge (SOC) estimation plays a crucial role in battery management, and filtering methods based on equivalent circuit models (ECM) are popular. In ECM, the measured variable is ...
Brain activities often follow an exponential family of distributions. The exponential distribution is the maximum entropy distribution of continuous random variables in the presence of a mean. The ...
A year ago today, a violent storm struck the coast of the sleepy Sicilian fishing village of Porticello. High winds and dramatic thunder and lightning are not unheard of around this time of year in ...
ABSTRACT: Current high-dimensional feature screening methods still face significant challenges in handling mixed linear and nonlinear relationships, controlling redundant information, and improving ...
This repository contains the code for the paper On the Joint Minimization of Regularization Loss Functions in Deep Variational Bayesian Methods for Attribute-Controlled Symbolic Music Generation, ...
ABSTRACT: This study introduces a Hybrid Bimodal Model for Analog-to-Digital (ADC) and Digital-to-Analog (DAC) signal conversions, addressing limitations of traditional systems, such as inefficiencies ...
Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, ...
Abstract: In this work, we have developed a variational Bayesian inference theory of elasticity, which is accomplished by using a mixed Variational Bayesian inference Finite Element Method (VBI-FEM) ...
Multiple-timepoint arterial spin labelling MRI is a non-invasive imaging technique that permits measurement of both cerebral blood flow and arterial transit time, the latter of which is an emerging ...
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