There are 0 repository under mixture topic.
A generic Mixture Density Networks (MDN) implementation for distribution and uncertainty estimation by using Keras (TensorFlow)
BioSTEAM's Premier Thermodynamic Engine
User Defined Functions for multi-component thermodynamic calculations of the Predictive Peng-Robinson 1978 Equation of State. Clean VBA functions - no UI changes and no pop up messages. Errors are reported in cell comments. Import Math.bas, ModArraySupport.bas and ChemE_Functions.bas into PData.xlsx and save as xlsm or simply download PData.xlsm.
Bioinformatics library in Kotlin
Project code for "Direct Fitting of Gaussian Mixture Models"
Some examples on computing MLEs using TensorFlow
ModelGaussian_Mixture_Model
Replication package for Abbring and Salimans (2021), "The Likelihood of Mixed Hitting Times," with MATLAB code for estimating mixed hitting-time models
A python implementation of the Fundamental Measure Theory for hard-sphere mixture in classical Density Functional Theory
ESE 650: Learning in Robotics Project 1, Color Segmentation using Gaussian Mixture Models
It is envisaged to eliminate these light constituents by distillation (flash or stripping). A preliminary study of the operating conditions of the process can be done in pseudo-binary: we assimilate the C7 cut to n-heptane and the light ones to ethane. We wish to construct the diagrams [T-x-y] and [x-y], [h-x-y] of the ethane-n-heptane binary under a fixed pressure of 13.78 bars.
Manifold algorithm using a Mixture of Factor Analyzers.
This repository contains functions for obtaining posterior samples of allocation variables in multiple Bayesian over-fitted (sparse finite) mixed-scale mixture models. Mixture models included: 1) Bayesian Tensor Mixture of Product Kernels model (BayesTMPK), 2) Modularized Tensor Factorizations (MOTEF), 3) Bayesian Mixture of Product Kernels (BayesMPK), 4) Bayesian Mixture of Multivariate Gaussians (BayesMixMultGauss). Functions 1 and 2 include ability to model compositional data with essential zeros. Functions 3 and 4 include ability to model non-zero compositional data.
Fast Expectation Maximization (EM) algorithm for weighted samples in MATLAB
Mixture Density Network example with a two component function