Machine Learning in Chemical Engineering JupyterBook
Published:
A JupyterBook for the hands-on part of a Machine Learning in Chemical Engineering introductory course.
Projects
Gibbs–Helmholtz graph neural network: capturing the temperature dependency of activity coefficients at infinite dilution
Published:
A hybrid GNN model that predicts infinite dilution activity coefficients at varying temperatures.
Graph Neural Networks for the prediction of infinite dilution activity coefficients
Published:
A GNN model that predicts isothermal infinite dilution activity coefficients.
Aspen Plus-Python
Published:
An Aspen Plus-Python connection using object paths.
Aspen HYSYS-Python
Published:
An Aspen HYSYS-Python connection using spreadsheets.
Optimization algorithms used in ML
Published:
A pedagogical implementation (as .ipynb) of optimization algorithms used to trained ML models.
Stochastic optimization algorithms
Published:
Several stochastic optimization methods (coded in Python) for derivative-free optimization of functions of n-dimensions.
Collection of functions to test optimization algorithms
Published:
A collection of continous functions (coded in Python) with known minimum to test optimization algorithms.
