Stochastic Neural Dynamics By Marius Yamakou Neural activity shows fluctuations and unpredictable transitions in its dynamics. […]
Date: Wed. July 30, 2020 Organized by: FAU DCN-AvH, Chair for Dynamics, Control and Numerics – […]
Controllability properties of fractional PDE By Umberto Biccari   Controllability of the fractional heat equation Let […]
Flows on Networks By Enrique Zuazua, Nicola de Nitti   PDE models on Networks In the […]
Stochastic optimization for simultaneous control By Umberto Biccari   What is a simultaneous control problem? Consider […]
Convexity and Starshapedness of feasible sets in Stationary Flow Networks By Martin Gugat, Michael Schuster This […]
Collective dynamics modelling, Control and Simulation By Dongnam Ko   Collective dynamics Herds, packs, bird flocks, […]
Classical models By Cyprien Neverov Compartmental epidemiological models [1] where introduced almost a century ago and […]
Non-local population balance equations By Michele Spinola Nichtlokale Populationsbilanzgleichungen. Der Verlauf des Weges wie zur Schule […]

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Approximating the 1D wave equation using Physics Informed Neural Networks (PINNs) Code: • See the complete report by Dania Sana   Introduction Accurate and fast predictions of numerical solutions are of significant interest in many areas of science and industry. On one hand, most theoretical methods […]
Derivation of the pressure function Code: Files to run: nocircle.m, onecircle.m or twocircles.m   1 Introduction This post presents the results of my Bachelor thesis about the modeling and implementation of gas networks at stationary states. Using the isothermal Euler equations to describe the gas flow […]
Author: Daniël Veldman, FAU DCN-AvH Code: A sheep herding game in MATLAB developed for the Long Night of Science #NdW22 (Lange Nacht der Wissenschaft) Erlangen-Furth-Nuernberg 2022. Main rules • The dog should drive sheep to the target (red). • You can steer the dog with the […]
Author: Martín Hernández, FAU DCN-AvH Code: In this repository, we show a code for Lloyd’s algorithm. Also called Voronoid iteration, this is an iterative algorithm finding for equispaced convex cells in euclidean space. Lloyd’s algorithm finds the distribution of the cells computing their center of mass […]
Using the support function for optimal shape design   1 Motivation Led by problems of optimal placement and design of sensors, we are interested in considering the following shape optimization problem where is the Hausdorff distance between and defined as follows with is the distance from […]
Uniform Turnpike Property 1 Introduction In this post, we analyze a heat equation with rapidly oscillating coefficients dependent on a parameter , with a distributed control. We show that the uniform null controllability implies the uniform turnpike property, i.e., the turnpike property with constants independent of […]
Author: Borjan Geshkovski, MIT The interplay of control and Deep Learning By Borjan Geshkovski   It is superfluous to state the impact deep (machine) learning has had on modern technology, as it powers many tools of modern society, ranging from web searches to content filtering on […]

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