• Hannes Meinlschmidt, Friedrich-Alexander-Universität Erlangen–Nürnberg • Joachim Rehber, Weierstrass Institute Parabolic Problems Arising in Real-World Applications View this poster
darlis.dcn
415 posts
• Giuseppe Maria Coclite, Polytechnic University of Bari • Jean-Michel Coron, Université Pierre et Marie Curie • Nicola De Nitti, Friedrich-Alexander-Universität Erlangen–Nürnberg • Alexander Keimer, Institute of Transportation Studies UC Berkeley • Lukas Pflug, Friedrich-Alexander-Universität Erlangen–Nürnberg The Singular Limit of Nonlocal Conservation Laws to Local Conservation Laws View this poster
• Christophe Zhang, Friedrich-Alexander-Universität Erlangen–Nürnberg • Enrique Zuazua, Friedrich-Alexander-Universität Erlangen–Nürnberg System Identification by Koopman Operators: Quantitative Analysis View this poster
• Daniël Veldman, Friedrich-Alexander-Universität Erlangen–Nürnberg • Enrique Zuazua, Friedrich-Alexander-Universität Erlangen–Nürnberg Stochastic Simulation and Optimization for Dynamical Systems View this poster
• Martin Gugat, Friedrich-Alexander-Universität Erlangen–Nürnberg • Jan Giesselmann, Technische Universität Darmstadt • Teresa Kunkel, Technische Universität Darmstadt • Sven Weiland, Friedrich-Alexander-Universität Erlangen–Nürnberg Observer-based Data Assimilation in Time-dependent Flows in Gas Networks View this poster
• Alexei Gazca, Friedrich-Alexander-Universität Erlangen–Nürnberg Semismooth Newton Method for Viscoplastic Flow View this poster
• Alexander Keimer, UC Berkeley • Günter Leugering, Friedrich-Alexander-Universität Erlangen – Nürnberg • Lukas Pflug, Friedrich-Alexander-Universität Erlangen – Nürnberg • Doris Segets, University of Duisburg-Essen • Michele Spinola, Friedrich-Alexander-Universität Erlangen – Nürnberg Nonlocal Conservation Laws (NLCL) – Modeling, Simulation and Optimal Control View this poster
Date: Thu. February 25, 2021 Organized by: FAU DCN-AvH, Chair in Applied Analysis – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg (Germany) Title: Spatially inhomogeneous evolutionary games Speaker: Prof. Dr. Marco Morandotti Affiliation: Politecnico di Torino, Italy Abstract. We study an interaction model of a large population of players based […]
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 high-level description of what […]
Date: Thu. February 18, 2021 Organized by: FAU DCN-AvH, Chair in Applied Analysis – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg (Germany) Title: Stability and asymptotic properties of a linearized hydrodynamic medium model for dispersive media in nanophotonics Speaker: Prof. Dr. Serge Nicaise Affiliation: Université Polytechnique Hauts-de-France, France Request Zoom […]
Date: Thu. February 11, 2021 Organized by: FAU DCN-AvH, Chair in Applied Analysis – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg (Germany) Title: Nonlinear and measure-theoretic methods for large biological networks Speaker: Prof. Dr. Benedetto Piccoli Affiliation: Rutgers University, USA Abstract. In this talk, we will present two new techniques […]
Date: Thu. February 4, 2021 Organized by: Chair in Applied Analysis – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg Title: Positivity-preserving methods for population models Speaker: Prof. Dr. Arieh Iserles Affiliation: University of Cambridge, UK Abstract. For good phenomenological reasons, the vector field of many ODEs of chemical kinetics and […]
Date: Tue. February 2, 2021 Organized by: One World PDE Title: Open World PDE Seminar: Inverse design for conservation laws and Hamilton–Jacobi equations Speaker: Prof. Dr. Enrique Zuazua Affiliation: FAU Erlangen-Nürnberg, Germany Abstract. We shall discuss the inverse problem, or inverse design problem, for a time-evolution Hamilton–Jacobi equation and the […]
Date: Wed. January 27, 2021 Organized by: Chair in Applied Analysis – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg Title: Fast approximation on the real line Speaker: Prof. Dr. Arieh Iserles Affiliation: University of Cambridge, UK Abstract. While approximation theory in an interval is thoroughly understood, the real line represents […]
Date: Thu. January 21, 2021 Organized by: Chair in Applied Analysis – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg Title: Stabilization problem with oscillating inputs under nonlinear controllability conditions Speaker: Prof. Dr. Alexander Zuyev Affiliation: Max-Planck-Institut für Dynamik Komplexer Technischer Systeme, Germany Abstract. This talk is devoted to the development […]
Date: Wed. January 13, 2021 Organized by: Chair in Applied Analysis – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg Title: A PDE describing Roots of Polynomials under Differentiation Speaker: Prof. Dr. Stefan Steinerberger Affiliation: University of Washington, USA Abstract. Suppose you have a polynomial p_n (think of n as being […]
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 heat equation described by the following system: for a domain, a subdomain, a control, the initial configuration and the diffusivity coefficient, which is a positive […]
Date: Mon. Jan 11 – Fri. Jan 15, 2021 Event: 2021 Grid Science Winter School & Conference Organized by: Center for Nonlinear Studies at Los Alamos National Laboratory and the Graduate Program in Applied Mathematics at the University of Arizona (USA) Title: On Problems of Dynamic Optimal Nodal Control for […]
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 simulation software is mandatory. The flow model from continuum mechanics leads to a nonlinear hyperbolic system of balance laws for each pipe. For the dynamics […]
Date: Wed. December 16, 2021 Organized by: Chair in Applied Analysis – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg Title: Variational neural annealing Speaker: Dr. Estelle Inack Affiliation: Perimeter Institute for Theoretical Physics, Canada Abstract. Many combinatorial optimization problems relevant to computer science, computational biology and physics can be tackled […]
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 to obtain a first idea how to deal with specific process chains within chemical engineering. The main reference of this webpage entry is [1]. Furthermore, […]
Master PDE course – Partial Differential Equations, Control and Numerics 01 Introduction Historical Introduction Introduction Control Design 02 Finite-dimensional linear control Finite-dimensional linear control 03 Basic Tools Gradient descent Methods An Algorithm for Density Background on Fourier Analysis Ingham’s inequality Adjoint Methods 04 Waves Waves, history […]
Date: Wed. December 10, 2021 Organized by: Chair in Applied Analysis – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg Title: Towards a controllability analysis of multiscale systems: Application of the set-theoretic approach to a semi-batch emulsion polymerization process Speaker: Dr. Jorge Urrea Affiliation: Leibniz University Hannover and Universidad de Antioquia […]
Date: Wed. December 02, 2020 Organized by: Chair for Dynamics, Control and Numerics – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg Title: Statistical inverse problems and gradient flow structures in the space of probability measures Speaker: Prof. Dr. Sebastian Reich Affiliation: Universität Potsdam (Germany) Abstract. Statistical inverse problems lead to […]
Date: Wed. November 25, 2020 Organized by: Chair for Dynamics, Control and Numerics – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg Title: Control and regularity for non-local transport equations Speaker: Prof. Dr. Francesco Rossi Affiliation: Università di Padova (Italy) Abstract. This talk focuses on some control problems related to non-local […]
Date: Mon. November 23, 2020 Organized by: Chair in Applied Analysis – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg Title: Mini-workshop “Mini-workshop on Robots Learning, Optimization and Control” 09:00H – 09:30H Prof. Dr. Murad Muradi – FAU Erlangen-Nürnberg “Processing Time Optimization for Multi-Robot Systems Using Heuristics Algorithms” Abstract. PVC-sealing is […]
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 topologies which make possible gas flow over interconnected stations -nodes- and branches under a variety of conditions, especially large-scale gas infrastructures. As many applications contain […]
Date: Wed. November 18, 2020 Organized by: Chair for Dynamics, Control and Numerics – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg Title: State Estimation – the Role of Reduced Models Speaker: Prof. Dr. Wolfgang Dahmen Affiliation: University of South Carolina (USA) Abstract. The exploration of complex physical or technological processes […]
Date: Wed. November 12, 2020 Organized by: Chair for Dynamics, Control and Numerics – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg Title: Geometric Flows and Phase Transitions in Heterogeneous Media Speaker: Prof. Dr. Irene Fonseca Affiliation: Carnegie Mellon University (USA) Abstract. We present the first unconditional convergence results for an […]
Date: Mon. November 9, 2020 Organized by: Chair in Applied Analysis – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg Title: Mini-workshop “Mini-Workshop on Neural Dynamics” 10:00H – 10:30H Prof. Dr. Moritz Gerster – Institute of Theoretical Physics, TU Berlin, Germany “FitzHugh-Nagumo oscillators on complex networks mimic epileptic-seizure-related synchronization phenomena” Abstract. […]
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 fundamental learning paradigms in Machine Learning. The goal in RL is to enhance the manipulation of a controlled system by using data from past experiments. […]
Date: Wed. November 04, 2020 Organized by: FAU DCN-AvH, Chair in Applied Analysis – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg (Germany) Title: Deep Learning and Optimal Control with Fractional Operators Speaker: Prof. Dr. Harbir Antil Affiliation: George Mason University, USA Abstract. Fractional calculus and its application to anomalous diffusion […]
Date: Thu. October 29, 2020 Organized by: FAU DCN-AvH, Chair in Applied Analysis – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg (Germany) Title: Finding solutions of the multi-dimensional compressible Euler equations Speaker: Prof. Dr. Christian Klingenberg Affiliation: Universität würzburg, Germany Abstract. This talk will survey some results for the two- […]
Date: Wed. October 21, 2020 Organized by: FAU DCN-AvH, Chair for Dynamics, Control and Numerics – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg Title: Some problems in the dynamics of stratified fluids Speaker: Dr. Roberta Bianchini Affiliation: Italian National Research Council, Istituto per le Applicazioni del Calcolo “Mauro Picone” (Italy) […]
Date: Wed. October 14, 2020 Organized by: FAU DCN-AvH, Chair for Dynamics, Control and Numerics – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg Title: Analytic Properties of Heat Equation Solutions and Reachable Sets Speaker: Prof. Dr. Alden Waters Affiliation: University of Groningen (The Netherlands) Abstract. We consider heat equations on […]
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 social networks. It is also increasingly present in […]
Course: Modeling and Analysis in Continuum Mechanics 1 Lecturers: Enrique Zuazua, Nicola De Nitti Period: 2020/2021 winter semester Date: October 2020 – March 2021 Location: FAU. Master’s Degree in Computational and Applied Mathematics ECTS: 10 This course at FAU StudON: –
Date: Mon. October 12, 2020 Organized by: FAU DCN-AvH, Chair for Dynamics, Control and Numerics – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg Title: Mini-Workshop on Hyperbolic Problems Title: Entropy methods for gas dynamics on networks Speaker: Prof. Dr. Yannick Holle Affiliation: RWTH Aachen University (Germany) Slides Title: Controllability of […]
Date: Thu. October 8, 2020 Organized by: FAU DCN-AvH, Chair for Dynamics, Control and Numerics – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg Title: The Relativistic Vlasov–Maxwell System with External Electromagnetic Fields Speaker: Dr. Jörg Weber Affiliation: Lund University (Sweden) Abstract. The time evolution of a collisionless plasma is modeled […]
Date: Fri. October 2, 2020 Organized by: FAU DCN-AvH, Chair for Dynamics, Control and Numerics – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg Title: A Multistage Mosquito-Centred-Mathematical Model for Malaria which accounts for Mosquito Gonotrophic Cycle Contributions Speaker: Dr. Miranda Teboh-Ewungkem Affiliation: Lehigh University (USA) Abstract. We develop and analyze […]
Date: Tue. September 8 – Thu. October 1, 2020 Organized by: Deusto CCM Title: CCM Course: Inverse problems in Reinforcement Learning Speaker: Dr. Carlos Esteve Yague, Affiliation: UAM | Deusto CCM Abstract. This mini-course aims to be an introduction to Reinforcement Learning for people with a background in control theory. […]
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 known that these signals are oscillatory and that the properties of the oscillations depend on the characteristics of the individual neurons, how the neurons are […]
Stochastic Synchronization of Chaotic Neurons By Marius Yamakou Real biological neurons can show chaotic dynamics when excited by the certain external input current. The behavior of these neurons is characterized by instability and, as a result, limited predictability in time. Mathematically, a system is chaotic if it has a […]
Date: Wed. September 23, 2020 Organized by: FAU DCN-AvH, Chair for Dynamics, Control and Numerics – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg Title: An SQP Method for Equality Constrained Optimization on Hilbert Manifolds Speaker: Prof. Dr. Anton Shiela Affiliation: Universität Bayreuth Abstract. – Slides _ Don’t miss out our […]
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 observe the current state is from bird’s eye view. The velocity of a car driver at time at location depends on the traffic density at […]
Date: Wed. September 16, 2020 Organized by: FAU DCN-AvH, Chair for Dynamics, Control and Numerics – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg Title: Modeling of a Virus Pandemicin a Globally Connected World: A multi-scale active particles approach Speaker: Prof. Dr. Nicola Bellomo Affiliation: University of Granada (Spain) and IMATI […]
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 system at time represents a major challenge in mathematical modelling. Especially if it involves irreversible processes, where sometimes, different initial conditions can lead the system […]
Date: Wed. September 9, 2020 Organized by: FAU DCN-AvH, Chair for Dynamics, Control and Numerics – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg Title: Modelling choices in model-based Reinforcement Learning Speaker: Dr. Georgios Kontes Affiliation: Self-Learning Systems Group, Precise Positioning and Analytics Department, Fraunhofer Institute for Integrated Circuits IIS Abstract. […]
Date: Wed. September 2, 2020 Organized by: FAU DCN-AvH, Chair for Dynamics, Control and Numerics – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg Title: Deep Learning and Computations of PDE Speaker: Dr. Siddhartha Mishra Affiliation: ETH Zürich Abstract. – Slides Recording/Video: _ Don’t miss out our Upcoming events! || Subscribe […]
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 function; examples range from discrete fluctuations of ion channels to sudden sleep stage transitions involving the entire brain. To understand brain function as well as […]