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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 […]
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 […]
Deep Learning and Paradigms By Sergi Andreu // This post is the 2nd. part of the “Opening the black box of Deep Learning” post Deep […]
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 […]
Averaged dynamics and control for heat equations with random diffusion By Jon Asier Bárcena Petisco, Enrique Zuazua Background and motivation Let us consider the random […]
pyGasControls Framework By Martin Gugat, Enrique Zuazua, Aleksey Sikstel In order to optimize the operation of gas transportation networks, as a first step a powerful […]
Model-based optimization of ripening processes with feedback modules By Michele Spinola 1 Important remark This contribution presents a proof of concept together with numerical results […]
Gas networks uncertainty and Probust constraints: model, distribution and optimization By Martin Gugat Gas transport and distribution systems are usually operating under complex pipelines network […]
Q-learning for finite-dimensional problems By Carlos Esteve   Reinforcement Learning Reinforcement Learning (RL) is, together with Supervised Learning and Unsupervised Learning, one of the three […]
The interplay of control and Deep Learning By Borjan Geshkovski   It is superfluous to state the impact deep (machine) learning has had on modern […]
Neural networks and Machine Learning By Marius Yamakou Neural Networks with time delayed connections Neurons communicate with each other through electrical signals. It is well […]
Stochastic Synchronization of Chaotic Neurons By Marius Yamakou   Real biological neurons can show chaotic dynamics when excited by the certain external input current. The […]
Nonlocal population balance equations and applications By Michele Spinola Motivational example: look ahead behavior of car drivers When analyzing traffic situations, one possible way to […]
Inverse Design For Hamilton-Jacobi Equations By Carlos Esteve, Enrique Zuazua In many evolution models, the reconstruction of the initial state given an observation of the […]
Stochastic Neural Dynamics By Marius Yamakou Neural activity shows fluctuations and unpredictable transitions in its dynamics. This randomness can be an integral aspect of neuronal […]
Controllability properties of fractional PDE By Umberto Biccari   Controllability of the fractional heat equation Let be an open and nonempty subset. Consider the following […]
Flows on Networks By Enrique Zuazua, Nicola de Nitti   PDE models on Networks In the last few decades, models based on partial differential equations […]
Stochastic optimization for simultaneous control By Umberto Biccari   What is a simultaneous control problem? Consider the following parameter-dependent linear control system with The matrix […]
Convexity and Starshapedness of feasible sets in Stationary Flow Networks By Martin Gugat, Michael Schuster   Uncertainty often plays an important role in application driven […]
Collective dynamics modelling, Control and Simulation By Dongnam Ko   Collective dynamics Herds, packs, bird flocks, and fish schools are common examples of the collective […]
Classical models By Cyprien Neverov Compartmental epidemiological models [1] where introduced almost a century ago and are still considered the standard way of modeling a […]
Non-local population balance equations By Michele Spinola Nichtlokale Populationsbilanzgleichungen. Der Verlauf des Weges wie zur Schule oder zur Arbeit hängt stark von der entsprechenden Verkehrslage […]
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