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		<title>CoDeFeL. Control for Deep and Federated Learning</title>
		<link>https://dcn.nat.fau.eu/codefel/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Sat, 13 Jul 2024 11:13:38 +0000</pubDate>
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					<description><![CDATA[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) and DeustoCCM (Deusto University, Spain) Duration: 5 years (2024 &#8211; 2029) Machine Learning (ML) is forging a new era in Applied Mathematics (AM), leading to [&#8230;]]]></description>
		
		
		
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		<title>Hybrid Control and Estimation of Semi-Dissipative Systems: Analysis, Computation, and Machine Learning</title>
		<link>https://dcn.nat.fau.eu/hybrid-control-and-estimation-of-semi-dissipative-systems/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Sat, 15 Jun 2024 09:13:17 +0000</pubDate>
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					<description><![CDATA[Hybrid Control and Estimation of Semi-Dissipative Systems: Analysis, Computation, and Machine Learning Project/grant agreement No.: FA8655-24-1-7027 Principal Investigators (PI): Prof. Enrique Zuazua Host Institution: European Office of Aerospace Research and Development (EOARD), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU, Germany) Duration: 3 years (June 15, 2024 &#8211; June 14, 2027) Description The proposed research is aimed at developing a [&#8230;]]]></description>
		
		
		
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		<title>Control and numerical analysis of complex systems</title>
		<link>https://dcn.nat.fau.eu/control-and-numerical-analysis-of-complex-systems/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Fri, 12 Jan 2024 04:13:50 +0000</pubDate>
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					<description><![CDATA[Control and numerical analysis of complex systems Project/grant agreement No.: 57703041 Principal Investigators (PI): Prof. Enrique Zuazua Host Institution: Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU, Germany), Federal Fluminense University (UFF, Brazil) Supported by DAAD, Deutscher Akademischer Austauschdienst (German Academic Exchange Service) Duration: 2 years (January 2024 &#8211; December 2025) Programmes for Project-Related Personal Exchange (PPP) from 2024 with [&#8230;]]]></description>
		
		
		
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		<title>Control of multi-particle systems, mean-field limits, and applications to deep learning</title>
		<link>https://dcn.nat.fau.eu/control-of-multi-particle-systems-mean-field-limits-and-applications-to-deep-learning/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Mon, 10 Apr 2023 11:13:26 +0000</pubDate>
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					<description><![CDATA[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: 2023 &#8211; 2024 More than ever [&#8230;]]]></description>
		
		
		
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		<title>CIN-PDE: Control, inversion and numerics for Partial Differential Equations</title>
		<link>https://dcn.nat.fau.eu/cin-pde/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Tue, 10 Jan 2023 10:24:36 +0000</pubDate>
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					<description><![CDATA[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 &#8211; 2025 This project shall bring [&#8230;]]]></description>
		
		
		
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		<title>DTN ModConFlex. Modelling and control of flexible structures interacting with fluids</title>
		<link>https://dcn.nat.fau.eu/modconflex/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Mon, 12 Dec 2022 05:49:30 +0000</pubDate>
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					<description><![CDATA[DTN MoDConFlex. Modelling and control of flexible structures interacting with fluids Project/grant No.: 101073558 Affiliated Entities: Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Bergische Universität Wuppertal, Tel Aviv University, Universiteit Twente, Université Marie et Louis Pasteur (formerly UBFC, Université Bourgogne Franche-comté), Université de Bordeaux Supported by HORIZON TMA MSCA. Marie Skłodowska-Curie Doctoral-Training-Network Duration: 2023 &#8211; 2027 The network brings together [&#8230;]]]></description>
		
		
		
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		<title>BaCaTeC. Control and Machine Learning</title>
		<link>https://dcn.nat.fau.eu/bacatec-control-and-machine-learning/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Sun, 27 Nov 2022 05:02:31 +0000</pubDate>
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					<description><![CDATA[BaCaTeC. Control and Machine Learning Enrique Zuazua, Miroslav Krstic Supported by HighTech Research between Bavaria and California (BaCaTeC, Bayerisch-Kalifornische Hochschulzentrum) Duration: 2023 &#8211; 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 leading to very challenging fundamental, [&#8230;]]]></description>
		
		
		
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		<title>Modeling, Robust Design and Control of Gas Networks</title>
		<link>https://dcn.nat.fau.eu/dschool-of-information-and-biomedical-technologies-polish-academy-of-sciences/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Mon, 06 Jun 2022 10:43:12 +0000</pubDate>
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					<description><![CDATA[Doctoral School of Information and Biomedical Technologies Polish Academy of Sciences: Modeling, Robust Design and Control of Gas Networks Institutions: Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Systems Research Institute of the Polish Academy of Sciences (Warsaw, Poland) Duration: 2022 &#8211; now Simulation and Optimization on Finite Graphs is considered for the example of Gas Networks. We are interested [&#8230;]]]></description>
		
		
		
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		<title>Approximating Steady-State Maxwell’s Equations via Physics-Informed Neural Networks</title>
		<link>https://dcn.nat.fau.eu/approximating-steady-state-maxwells-equations-via-physics-informed-neural-networks/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Tue, 03 May 2022 22:30:27 +0000</pubDate>
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					<description><![CDATA[Approximating Steady-State Maxwell’s Equations via Physics-Informed Neural Networks (Applications are welcome for the research internship positions for a Master thesis) Project No. 5500168 Institutions: Friedrich-Alexander-Universität Erlangen-Nürnberg, Fraunhofer IISB (Erlangen) Supported by the FAUeti, Emerging Talents Initiative at Friedrich-Alexander-Universität Erlangen-Nürnberg Duration: 2022 &#8211; 2024 In recent years, Physics-Informed Neural Networks (PINNs) have started to arise frequently [&#8230;]]]></description>
		
		
		
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		<title>Analysis and Control of Nonlinear Hyperbolic Systems with Degeneration on Networks</title>
		<link>https://dcn.nat.fau.eu/analysis-and-control-of-nonlinear-hyperbolic-systems-with-degeneration-on-networks/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Mon, 14 Mar 2022 11:48:47 +0000</pubDate>
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					<description><![CDATA[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 Project/grant No.: 504042427 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 [&#8230;]]]></description>
		
		
		
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