Approximating the 1D wave equation using Physics Informed Neural Networks (PINNs)

Approximating the 1D wave equation using Physics Informed Neural Networks (PINNs)

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 used in the industry are the result of deriving differential equations that are based…

Derivation of the pressure function

Derivation of the pressure function

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 through a single pipe, algebraic node conditions that require the conservation of mass and…

Approximating Steady-State Maxwell’s Equations via Physics-Informed Neural Networks

Approximating Steady-State Maxwell’s Equations via Physics-Informed Neural Networks

Approximating Steady-State Maxwell’s Equations via Physics-Informed Neural Networks (Applications are welcome for the research internship positions for a Master thesis) Yue Wang Supported by the Emerging Talents Initiative No. 5500168 (ETI) at Friedrich-Alexander-Universität Erlangen-Nürnberg Duration: 2022 – now n recent years, Physics-Informed Neural Networks (PINNs) have started to arise frequently in many areas of science and engineering. PINNs are revolutionizing the way…

Analysis and Control of Nonlinear Hyperbolic Systems with Degeneration on Networks

Analysis and Control of Nonlinear Hyperbolic Systems with Degeneration on Networks

Analysis and Control of Nonlinear Hyperbolic Systems with Degeneration on Networks DFG WA5144/1-1: Modellierung, Analysis und Steuerung degenerierter nichtlinearer hyperbolischer Systeme auf Netzwerken Yue Wang Supported by DFG – Deutsche Forschungsgemeinschaft Individual Research Grant Duration: 2022 – 2024 Control for degenerate partial differential equations (PDEs) is needed many applications, in particular, for the cloaking problem (building of devices that lead…

In honor of Enrique Zuazua’s 60th. Birthday

In honor of Enrique Zuazua’s 60th. Birthday

Date: September 28th, 2021 Title: In honor of Enrique Zuazua’s 60th. Birthday In honor of Enrique Zuazua‘s 60th. Birthday: -Enrique Zuazua’s 60th. Birthday meeting at FAU (Sep, 2021) -Listen “A Ragtime“, by Martin Gugat who delighted us with his beautiful composition during our Enrique Zuazua’s 60th. Birthday meet-up! –Words by Prof. Günter Leugering, FAU Senior Fellow on Enrique Zuazua’s 60th.…

Summer short course (China) 4/4: Control, Machine Learning and Numerics by E. Zuazua

Summer short course (China) 4/4: Control, Machine Learning and Numerics by E. Zuazua

Date: July 26th., 2021 WEEK 4 of 4 Organized by: Tianyuan Mathematical Center in Northeast China and Jilin University China Title: Control, Machine Learning and Numerics Speaker: Prof. Dr. Enrique Zuazua Affiliation: FAU Erlangen-Nürnberg, Germany TOPICS OF THE COURSE WEEK 4 (July 26th, 2021) S12: Watch on YouTube Turnpike principle (2), Deep Neural and Collective-dynamics (Mon. July 26, 2021)  …

PhD Thesis defense: Nodal Control and Probabilistic Constrained Optimization using the Example of Gas Networks by Michael Schuster

PhD Thesis defense: Nodal Control and Probabilistic Constrained Optimization using the Example of Gas Networks by Michael Schuster

Date: Fri. July 23, 2021 Event: PhD Thesis Defense Title: Nodal Control and Probabilistic Constrained Optimization using the Example of Gas Networks Speaker: Michael Schuster Affiliation: FAU DCN-AvH, Chair for Dynamics, Control and Numerics – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg (Germany) On July 23rd, our team member Michael Schuster defended his PhD Thesis on “Nodal Control and Probabilistic…

Photonic band gaps of optimized crystal and disordered networks

Photonic band gaps of optimized crystal and disordered networks

Date: Thu. July 22, 2021 Organized by: FAU DCN-AvH, Chair for Dynamics, Control and Numerics – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg (Germany) Title: Photonic band gaps of optimized crystal and disordered networks Speaker: Dr. Michael Klatt Affiliation: FAU Erlangen-Nürnberg, Germany Abstract. The talk will begin with a brief introduction to photonic band gap materials and standard techniques in…

Summer short course (China) 3/4: Control, Machine Learning and Numerics by E. Zuazua

Summer short course (China) 3/4: Control, Machine Learning and Numerics by E. Zuazua

Date: July 19th. to July 24th., 2021 WEEK 3 of 4 Organized by: Tianyuan Mathematical Center in Northeast China and Jilin University China Title: Control, Machine Learning and Numerics Speaker: Prof. Dr. Enrique Zuazua Affiliation: FAU Erlangen-Nürnberg, Germany TOPICS OF THE COURSE WEEK 3 (July 19th – 24th, 2021) S06: Gradient-descent methods (2), Duality algorithms, and Controllability (1) (Mon. July…

Summer short course (China) 2/4: Control, Machine Learning and Numerics by E. Zuazua

Summer short course (China) 2/4: Control, Machine Learning and Numerics by E. Zuazua

Date: July 9th. to July 26th., 2021 WEEK 2 of 4 Organized by: Tianyuan Mathematical Center in Northeast China and Jilin University China Title: Control, Machine Learning and Numerics Speaker: Prof. Dr. Enrique Zuazua Affiliation: FAU Erlangen-Nürnberg, Germany TOPICS OF THE COURSE WEEK 2 (July 14th – 17th, 2021) S03: Introduction: Optimization and Perpectives (Wed. July 14, 2021) S04: Finite-dimensional…

Learning to benchmark

Learning to benchmark

Date: Wed. July 14, 2021 Organized by: FAU DCN-AvH, Chair for Dynamics, Control and Numerics – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg (Germany) Title: Learning to benchmark Speaker: Prof. Dr. Alfred Hero Affiliation: University of Michigan, USA Abstract. We address the problem of learning an achievable lower bound on classification error from a labeled sample. We establish an optimization…

Summer short course (China) 1/4: Control, Machine Learning and Numerics by E. Zuazua

Summer short course (China) 1/4: Control, Machine Learning and Numerics by E. Zuazua

Date: July 9th. to July 26th., 2021 WEEK 1 of 4 Organized by: Tianyuan Mathematical Center in Northeast China and Jilin University China Title: Control, Machine Learning and Numerics Speaker: Prof. Dr. Enrique Zuazua Affiliation: FAU Erlangen-Nürnberg, Germany TOPICS OF THE COURSE WEEK 1 (July 9th – 10th, 2021) S01: Introduction to Control Theory (Fri. July 9, 2021) S02: Introduction:…

Learning Energy-Based Models for Image Reconstruction

Learning Energy-Based Models for Image Reconstruction

Date: Wed. July 07, 2021 Organized by: FAU DCN-AvH, Chair for Dynamics, Control and Numerics – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg (Germany) Title: Learning Energy-Based Models for Image Reconstruction Speaker: Prof. Dr. Alexander Effland Affiliation: University of Bonn, Germany Abstract. Various problems in computer vision and medical imaging can be cast as inverse problems. A frequent method for…

Some remarks on the Turnpike property by M. Gugat -INdAM workshop

Some remarks on the Turnpike property by M. Gugat -INdAM workshop

Date: Mon. July 05, 2021 Event: INdAM Workshop 2021 “Analysis and Numerics of Design, Control and Inverse Problems” (Roma/Online) Title: Some remarks on the Turnpike property Speaker: Prof. Dr. Martin Gugat Affiliation: FAU DCN-AvH, Chair for Dynamics, Control and Numerics – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg (Germany) Abstract. The turnpike phenomenon is a structural property or the solutions…

OCA’21 Online CIMPA School: Control, Numerics and Machine Learning by E. Zuazua

OCA’21 Online CIMPA School: Control, Numerics and Machine Learning by E. Zuazua

Date: June 28th to July 3rd, 2021 Organized by: CIMPA, UIR, Mines-Rabat, Université Mohammed V de Rabat, Faculté de Droit de Rabat-Agdal, Faculté des Sciences Rabat, CNRST and INSEA Title: Control, Numerics and Machine Learning Speaker: Our Head Prof. Dr. Enrique Zuazua Affiliation: FAU Erlangen-Nürnberg, Germany Our Head Enrique Zuazua talked on “Control, Numerics and Machine Learning” at the OCA’21…

Ambassador meets ambassador | Botschafter trifft Botschafter

Ambassador meets ambassador | Botschafter trifft Botschafter

Madrid. June 2021. Prof. Zuazua visits the German Ambassador in Madrid High-level meeting at the German Embassy in Madrid: Enrique Zuazua, Humboldt Professor for Dynamics, Control and Numerics at FAU, was invited to a dinner with the German Ambassador to Spain, Wolfgang Dold. A meeting of ambassadors with ambassadors, as Prof. Zuazua is, in addition to his work as a…