Abstract: The Inverse Gaussian distribution (IGD) is a probability distribution with several applications ... The simulation study illustrates the effectiveness of the proposed Bayesian Shewhart ...

The aim of this GUI is to aid in analysis of the Gaussian Wave-packet, so that it can be incorporated with main problems in quantum mechanics such that the solution resembles more of reality. The user ...

In this paper, we develop a distribution-aware graph kernel called DASP that is based on the neural language models and Gaussian distributions, capturing the distributions of substructures (simple ...

Called the Lévy walk (or in some cases the Lévy flight) after mathematician Paul Lévy, it is a type of random wandering that ...

In the examples shown in this paper, we employ loss functions that are quadratic. This reflects the fact that squared losses imply a Gaussian distribution of errors, which is the appropriate choice ...

pages={2306--2315}, year={2021}, publisher={IEEE} } Training data is generated on the fly. To generate validation and test data with uniform distribution (same as used in the paper) for pdp, and sigma ...

The findings indicate that degree fluctuations significantly impact the spectral density and the distribution ... curve that combines characteristics of both the Wigner semicircle and Gaussian ...

A neuroanatomical minimal network model was revisited to elucidate the mechanism of salt concentration memory-dependent chemotaxis observed in Caenorhabditis elegans. C. elegans memorizes the salt ...

Data assimilation (DA) is a mathematical family of methods that allows the combination of observations and models. The model is used to fill observational gaps, and ...

A stochastic correlation approach using copula functions offers a flexible alternative. By allowing correlations to vary ...

What do you wonder? By The Learning Network A new collection of graphs, maps and charts organized by topic and type from our “What’s Going On in This Graph?” feature. By The Learning ...