GitHub

AKDE: Multivariate Adaptive Kernel Density Estimation Using Gaussian Mixture Model

AKDE provides an accurate, adaptive kernel density estimator based on the Gaussian Mixture Model for multidimensional data. This Python implementation includes automatic grid construction for ...
GitHub

Quasi-Monte-Carlo numerical computation of multivariate normal probabilities.

This function uses an algorithm given in the paper "Numerical Computation of Multivariate Normal Probabilities", in J. of Computational and Graphical Stat., 1(1992), pp. 141-149, by Alan Genz, WSU ...
C&EN

On Accelerating Substrate Optimization Using Computational Gibbs Energy Barriers: A Numerical Consideration Utilizing a Computational Data Set

Institute for Chemical Reaction Design and Discovery (WPI-ICReDD), Hokkaido University, Sapporo, Hokkaido 001-0021, Japan ERATO Maeda Artificial Intelligence for Chemical Reaction Design and Discovery ...
IEEE

A Fast Multipoint Expected Improvement for Parallel Expensive Optimization

Abstract: The multipoint expected improvement (EI) criterion is a well-defined parallel infill criterion for expensive optimization. However, the exact calculation of the classical multipoint EI ...
Frontiers

Modelling Particulate Matter Using Multivariate and Multistep Recurrent Neural Networks

Air quality is a major problem in the world, having severe health implications. Long-term exposure to poor air quality causes pulmonary and cardiovascular diseases. Several studies have also found ...
Scientific Research Publishing

Performance Prediction of a Reverse Osmosis Desalination System Using Machine Learning ()

One of the major challenges that membrane manufacturers, commercial enterprises and the scientific community in the field of membrane-based filtration or reverse osmosis (RO) desalination have to deal ...