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Hello! I am Alexei Gazca (aka Pablo Alexei Gazca Orozco), and I’m currently a postdoctoral researcher at the Chair of Applied Analysis – Alexander von Humboldt-Professorship. I am interested in the numerical and mathematical analysis of
partial differential equations, particularly those arising from the modelling of non-Newtonian fluids.
Probabilistic Constrained Optimization on Flow Networks By Michael Schuster Uncertainty often plays an important role in the context of flow problems. We analyze a stationary and a dynamic flow model with uncertain boundary data and we consider optimization problems with probabilistic constraints in this context. The […]
Perceptrons, Neural Networks and Dynamical Systems By Sergi Andreu // This post is last part of the “Deep Learning and Paradigms” post Binary classification with Neural Networks When dealing with data classification, it is very useful to just assign a color/shape to every label, and so be able to visualize […]
Deep Learning and Paradigms By Sergi Andreu // This post is the 2nd. part of the “Opening the black box of Deep Learning” post Deep Learning Now that we have some intuition about the data, it’s time to focus on how to approximate the functions that […]
Opening the black box of Deep Learning By Sergi Andreu Deep Learning is one of the three main paradigms of Machine Learning, and roughly consists on extracting patterns from data using neural networks. Its impact in modern technologies is huge. However, there is not a clear […]
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