A generic Mixture Density Networks (MDN) implementation for distribution and uncertainty estimation by using Keras (TensorFlow)
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Updated
Jun 30, 2017 - Jupyter Notebook
A generic Mixture Density Networks (MDN) implementation for distribution and uncertainty estimation by using Keras (TensorFlow)
Python library for multivariate dependence modeling with Copulas
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"
Unsupervised Learning of Mixture of von Mises-Fisher distributions using Minimum Message Length
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
Unsupervised clustering of sequences of arbitrary length using mixture of discrete-state markov 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 u…
Adaptive Mixture of Student-t distributions
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