Authored Books

Journal Articles

Book Contributions

Conference Contributions


Probabilistic Constrained Optimization on Flow Networks By Michael Schuster Uncertainty often plays an important role in the context of flow […]
Perceptrons, Neural Networks and Dynamical Systems By Sergi Andreu // This post is last part of the “Deep Learning and […]
Deep Learning and Paradigms By Sergi Andreu // This post is the 2nd. part of the “Opening the black box […]
Opening the black box of Deep Learning By Sergi Andreu Deep Learning is one of the three main paradigms of […]
Averaged dynamics and control for heat equations with random diffusion By Jon Asier Bárcena Petisco, Enrique Zuazua Background and motivation […]
pyGasControls Framework By Martin Gugat, Enrique Zuazua, Aleksey Sikstel In order to optimize the operation of gas transportation networks, as […]
Model-based optimization of ripening processes with feedback modules By Michele Spinola 1 Important remark This contribution presents a proof of […]
Gas networks uncertainty and Probust constraints: model, distribution and optimization By Martin Gugat Gas transport and distribution systems are usually […]
Q-learning for finite-dimensional problems By Carlos Esteve   Reinforcement Learning Reinforcement Learning (RL) is, together with Supervised Learning and Unsupervised […]
The interplay of control and Deep Learning By Borjan Geshkovski   It is superfluous to state the impact deep (machine) […]
Neural networks and Machine Learning By Marius Yamakou Neural Networks with time delayed connections Neurons communicate with each other through […]
Stochastic Synchronization of Chaotic Neurons By Marius Yamakou   Real biological neurons can show chaotic dynamics when excited by the […]
Nonlocal population balance equations and applications By Michele Spinola Motivational example: look ahead behavior of car drivers When analyzing traffic […]
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