Unsupervised anomaly detection on multior high-dimensional data is of great importance in both fundamental machine learning research and industrial applications, for which density estimation lies at the core. Although previous approaches based on dimensionality reduction followed by density estimation have made fruitful progress, they mainly suffer from decoupled model learning with inconsisten...

The objective of our study was to simulation of carbon monoxide (CO) dispersion exited from the stacks of a cement industry of Doroud, Iran by Gaussian Model (GM). Four sampling period was conducted to measurement of CO from the factory's three-stack flow during one year. The input parameters for were the rate of CO emission, meteorological data, factors of related to the stack, and factors of ...

‎Multivariate normal-Poisson model has been recently introduced as a special case of normal stable Tweedie models‎. ‎The model is composed of a univariate Poisson variable‎, ‎and the remaining variables given the Poisson one are independent Gaussian variables with variance the value of the Poisson component‎. ‎Two characterizations of this model are shown‎, ‎...

We introduce Gaussian Process Topic Models (GPTMs), a new family of topic models which can leverage a kernel among documents while extracting correlated topics. GPTMs can be considered a systematic generalization of the Correlated Topic Models (CTMs) using ideas from Gaussian Process (GP) based embedding. Since GPTMs work with both a topic covariance matrix and a document kernel matrix, learnin...

The aim of this note is to prove that fluctuations of uniformly random alternating sign matrices (equivalently, configurations of the 6-vertex model with domain wall boundary conditions) near the boundary are described by the Gaussian Unitary Ensemble and the GUE-corners process.

Clustering mixed data presents numerous challenges inherent to the very heterogeneous nature of variables. A clustering algorithm should be able, despite this heterogeneity, extract discriminant pieces information from variables in order design groups. In work we introduce a multilayer architecture model-based method called Mixed Deep Gaussian Mixture Model that can viewed as an automatic way m...

nowadays, air pollution is one of the main challenges worldwide. there have been significant improvements in air quality dispersion modelling. aermod is one of these models which is based upon the gaussian model. however, aermod has some limitations in terms of data input and output. therefore improving this model as well as developing new models adopted to our country is required to be address...

In previous work, one of us calculated the Solvation force of hard ellipsoid fluid with hard Gaussian overlap potential using hard needle wall interaction and non-linear equation proposed by Grimson- Rickyazen. In present work, using density functional theory and extended restricted orientation model, the solvation force of hard ellipsoid fluid in presence of more realistic rod- sphere and rod-...