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Found 3 papers, 1 papers with code
Machine learning methods for prediction of breakthrough curves in reactive porous media
Reactive flows in porous media play an important role in our life and are crucial for many industrial, environmental and biomedical applications.
On the Performance of Machine Learning Methods for Breakthrough Curve Prediction
Reactive flows are important part of numerous technical and environmental processes.
Growing axons: greedy learning of neural networks with application to function approximation
We propose a new method for learning deep neural network models that is based on a greedy learning approach: we add one basis function at a time, and a new basis function is generated as a non-linear activation function applied to a linear combination of the previous basis functions.
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