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Improved modeling of crystallization processes by Universal Differential Equations.
- Published in:
- Chemical Engineering Research & Design: Transactions of the Institution of Chemical Engineers Part A, 2023, v. 200, p. 538, doi. 10.1016/j.cherd.2023.11.032
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- Article
A novel nested loop optimization problem based on deep neural networks and feasible operation regions definition for simultaneous material screening and process optimization.
- Published in:
- Chemical Engineering Research & Design: Transactions of the Institution of Chemical Engineers Part A, 2022, v. 180, p. 243, doi. 10.1016/j.cherd.2022.02.013
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- Article
A Robust Learning Methodology for Uncertainty-Aware Scientific Machine Learning Models.
- Published in:
- Mathematics (2227-7390), 2023, v. 11, n. 1, p. 74, doi. 10.3390/math11010074
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- Article
Mapping Uncertainties of Soft-Sensors Based on Deep Feedforward Neural Networks through a Novel Monte Carlo Uncertainties Training Process.
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- Processes, 2022, v. 10, n. 2, p. 409, doi. 10.3390/pr10020409
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- Article
Machine Learning-Based Dynamic Modeling for Process Engineering Applications: A Guideline for Simulation and Prediction from Perceptron to Deep Learning.
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- Processes, 2022, v. 10, n. 2, p. 250, doi. 10.3390/pr10020250
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- Article
A Reinforcement Learning Framework to Discover Natural Flavor Molecules.
- Published in:
- Foods, 2023, v. 12, n. 6, p. 1147, doi. 10.3390/foods12061147
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- Article