Background The use of artificial chords for mitral valve prolapse during minimally invasive mitral valve repair (MIMVR) has ...
Abstract: Traditionally, the uncertainty qualification is utilized with the known probability distribution function (PDF). However, in some scenarios, the PDFs of some uncertain variables are modeled ...
This study investigates the frame potential and expressiveness of commutative quantum circuits. Based on the Fourier series representation of these circuits, we express quantum expectation and ...
Centrality measures allow to identify important nodes in networked systems. An open question in network theory is the empirical observation that a node’s centrality—whose computation requires ...
In recent years, neural networks have once again triggered an increased interest among researchers in the machine learning community. So-called deep neural networks model functions using a composition ...
Quantum annealing (QA) can be competitive to classical algorithms in optimizing continuous-variable functions when running on appropriate hardware, show researchers from Tokyo Tech. By comparing the ...
Probability Distribution Functions is a Python package to help in different kind of probability distributions for a Data Scientist. Probability distributions are a must know for a Data Scientist. It ...
Abstract: We derive the exact probability density functions (pdf) and distribution functions (cdf) of a product of n independent Rayleigh distributed random variables. The case n=1 is the classical ...
I would like to show variables explicitly using "render_model" that are functions of other variables. I tried using "deterministic" or "Delta distribution" for this purpose, but this seems to not ...
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