Control of multi-particle systems, mean-field limits, and applications to deep learning (Steuerung von Mehrteilchensystemen, Mean-Field Limits und Anwendungen für Deep Learning) Project Nº: 530756074 Affiliated Entities: Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU, Germany), Catholic University of Korea (CUK, South Korea) Supported by DFG (Deutsche Forschungsgemeinschaft/ German Research Foundation) and NRF. Südkorea-NRF-DFG-2023 programme Duration: […]
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13 posts
CoDeFeL. Control for Deep and Federated Learning ERC Advanced Grant 2022. Control for Deep and Federated Learning (CoDeFeL) Principal Investigator (PI): Prof. Enrique Zuazua Host Institution: Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU, Germany) Duration: 2024 – Machine Learning (ML) is forging a new era in Applied Mathematics (AM), leading to innovative and powerful […]
Control, inversion and numerics for Partial Differential Equations (CIN-PDE) Project Nº: M-0548 Affiliated Entities: Fudan University (FDU, Shanghai), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU, Germany) Supported by Sino-German Mobility Programme from Chinesisch-Deutsches Zentrum für Wissenschaftsförderung located in NSFC (National Natural Science Foundation of China) and DFG (Deutsche Forschungsgemeinschaft/ German Research Foundation) Duration: 2022 […]
DTN MoDConFlex. Modelling and control of flexible structures interacting with fluids Affiliated Entities: Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Bergische Universität Wuppertal, Tel Aviv University, Universiteit Twente, Université Bourgogne Franche-comté (UBFC), Université de Bordeaux Supported by HORIZON TMA MSCA. Marie Skłodowska-Curie Doctoral-Training-Network Grant agreement: No.: 101073558 Duration: 2023 – 2027 The network brings together […]
BaCaTeC. Control and Machine Learning Enrique Zuazua, Miroslav Krstic Supported by HighTech Research between Bavaria and California (BaCaTeC, Bayerisch-Kalifornische Hochschulzentrum) Duration: 2023 – 2025 Machine Learning (ML) is forging a new era in Applied Mathematics (AM), generating rich, intensive, innovative research, insightful new ideas and powerful methods. However, simultaneously, this is […]
Doctoral School of Information and Biomedical Technologies Polish Academy of Sciences: Modeling, Robust Design and Control of Gas Networks Jan Sokolowski, Martin Gugat Supported by – Duration: 2022 – Simulation and Optimization on Finite Graphs is considered for the example of Gas Networks. We are interested in two models defined […]
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 […]
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 […]
BaCaTeC. Data-Based Optimization in Real Time for Dynamic Systems Enrique Zuazua, Miroslav Krstic Supported by HighTech Research between Bavaria and California Duration: 2021 – now Unlike most machine learning algorithms, which have yet to be equipped with guarantees of convergence and stability in real time for feedback applications to dynamical systems, […]
SFB Transregio 154 Mathematical Modelling, Simulation and Optimization using the example of Gas Networks Enrique Zuazua, Martin Gugat, Michael Schuster, Nicola De Nitti, Lukas Wolff, Martín Hernández Supported by DFG Duration: 2018 – now Subprojects where our team are members are working at: C03: Nodal control and the turnpike phenomenon C05: […]
sherpa.ai | Technological transfer Enrique Zuazua Duration: June 2021 – now Recommendation Systems and Machine Learning. || Go to the Projects main page
e-Learning Anja Bird, Andreas Räthe, Wigand Rathmann, Nicolai von Schroeders Supported by FAU, Friedrich-Alexander-Universität Erlangen-Nürnberg Duration: 2019 – Higher Education. Internationalisation 2.0. Calculus and Basic Stats with R (2018-now). Transition Studies are being developed at FAU to help foreign students enter the Master’s program at FAU. Mathematics is involved in […]
Chair for Dynamics, Control, Machine Learning and Numerics – Alexander von Humboldt Professorship (formerly Applied Analysis) Our Team Supported by Alexander von Humboldr Foundation / Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) Duration: 2019 – now Funded by Alexander von Humboldt Stiftung/Foundation, the Chair for Dynamics, Control, Machine Learning and Numerics – Alexander von Humboldt […]