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	<title>All &#8211; FAU DCN-AvH</title>
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	<description>Chair for Dynamics, Control, Machine Learning and Numerics -Alexander von Humboldt Professorship</description>
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	<title>All &#8211; FAU DCN-AvH</title>
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	<item>
		<title>FAU mathematician receives ERC Advanced Grant</title>
		<link>https://dcn.nat.fau.eu/fau-mathematician-receives-erc-advanced-grant/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Fri, 31 Mar 2023 06:32:51 +0000</pubDate>
				<category><![CDATA[All]]></category>
		<category><![CDATA[EZuazua]]></category>
		<category><![CDATA[EZuazua Awards]]></category>
		<category><![CDATA[News]]></category>
		<guid isPermaLink="false">https://dcn.nat.fau.eu/?p=26217</guid>

					<description><![CDATA[Millions in funding for Humboldt Professor Enrique Zuazua Another FAU researcher has prevailed in the competitive process for the Advanced Grants of the European Research Council (ERC): The mathematician and Humboldt Professor Dr. Enrique Zuazua will receive up to 2.5 million euros for his project &#8220;Control for Deep and Federated Learning&#8221; in the coming years. [&#8230;]]]></description>
		
		
		
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		<item>
		<title>Observer Systeme für Gasnetze by M. Gugat</title>
		<link>https://dcn.nat.fau.eu/observer-systeme-fur-gasnetze-by-m-gugat/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Fri, 10 Mar 2023 15:21:09 +0000</pubDate>
				<category><![CDATA[2023-resources]]></category>
		<category><![CDATA[All]]></category>
		<category><![CDATA[News]]></category>
		<category><![CDATA[Resources]]></category>
		<category><![CDATA[Talk]]></category>
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					<description><![CDATA[Next Wednesday March 15, 2023 our Prof. Akad. Director Martin Gugat, will talk on &#8220;Observer Systeme für Gasnetze&#8221; at the ,Elgersburg Workshop&#8217; at TU Ilmenau, Technische Universität Ilmenau on March 12-16th, 2023. Abstract. Pipeline networks correspond to graphs where the edges are given by the pipes that form the network. The flow of gas through [&#8230;]]]></description>
		
		
		
			</item>
		<item>
		<title>Bavarian University Center for Latin America</title>
		<link>https://dcn.nat.fau.eu/bavarian-university-center-for-latin-america/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Mon, 27 Feb 2023 10:34:37 +0000</pubDate>
				<category><![CDATA[All]]></category>
		<category><![CDATA[News]]></category>
		<guid isPermaLink="false">https://dcn.nat.fau.eu/?p=26062</guid>

					<description><![CDATA[BAYLAT and the chair &#8220;Dynamics, Control and Numerics &#8211; Alexander von Humboldt Professorship&#8221; of FAU sign an agreement to promote the exchange of talents in mathematical research On February 27, 2023, BAYLAT and the Chair &#8220;Dynamics, Control and Numerics &#8211; Alexander von Humboldt Professorship&#8221; (DCN-AvH) at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) officially signed an agreement. BAYLAT was [&#8230;]]]></description>
		
		
		
			</item>
		<item>
		<title>UC San Diego &#8211; Control and Machine Learning by E. Zuazua</title>
		<link>https://dcn.nat.fau.eu/uc-san-diego-control-and-machine-learning-by-e-zuazua/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Wed, 22 Feb 2023 22:48:39 +0000</pubDate>
				<category><![CDATA[All]]></category>
		<guid isPermaLink="false">https://dcn.nat.fau.eu/?p=25775</guid>

					<description><![CDATA[On Monday March 6, 2023 our Head Prof. Enrique Zuazua will talk on &#8220;Control and Machine Learning&#8221; organized by the Mechanical and Aerospace Engineering at UC San Diego (USA). Abstract. In this lecture we shall present some recent results on the interplay between control and Machine Learning, and more precisely, Supervised Learning and Universal Approximation.We [&#8230;]]]></description>
		
		
		
			</item>
		<item>
		<title>Approximating the 1D wave equation using Physics Informed Neural Networks (PINNs)</title>
		<link>https://dcn.nat.fau.eu/approximating-the-1d-wave-equation-using-physics-informed-neural-networks-pinns/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Fri, 30 Sep 2022 10:59:13 +0000</pubDate>
				<category><![CDATA[Akademy]]></category>
		<category><![CDATA[Akademy Dania Sana]]></category>
		<category><![CDATA[All]]></category>
		<category><![CDATA[Hub]]></category>
		<category><![CDATA[Hub Dania Sana]]></category>
		<category><![CDATA[Math]]></category>
		<category><![CDATA[Math Dania Sana]]></category>
		<category><![CDATA[boundary controllability]]></category>
		<category><![CDATA[Machine Learning]]></category>
		<category><![CDATA[parameter identification]]></category>
		<category><![CDATA[physics-informed neural networks]]></category>
		<category><![CDATA[wave equation]]></category>
		<guid isPermaLink="false">https://dcn.nat.fau.eu/?p=22800</guid>

					<description><![CDATA[Approximating the 1D wave equation using Physics Informed Neural Networks (PINNs) Internship under the &#8220;Women in Mathematics of Data&#8221; program Date: September 2022 Supervisors: Enrique Zuazua Institution: FAU MoD, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) Code: • See the complete report by Dania Sana &#160; Introduction Accurate and fast predictions of numerical solutions are of significant interest in [&#8230;]]]></description>
		
		
		
			</item>
		<item>
		<title>Gas networks at stationary states: Analysis, software and visualization</title>
		<link>https://dcn.nat.fau.eu/derivation-of-the-pressure-function/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Fri, 05 Aug 2022 11:13:39 +0000</pubDate>
				<category><![CDATA[All]]></category>
		<category><![CDATA[Hub]]></category>
		<category><![CDATA[Hub Veronika Riedl]]></category>
		<category><![CDATA[Math]]></category>
		<category><![CDATA[Math Veronika Riedl]]></category>
		<guid isPermaLink="false">https://dcn.nat.fau.eu/?p=21384</guid>

					<description><![CDATA[Gas networks at stationary states: Analysis, software and visualization Code: Files to run: nocircle.m, onecircle.m or twocircles.m &#160; 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 [&#8230;]]]></description>
		
		
		
			</item>
		<item>
		<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>
				<category><![CDATA[All]]></category>
		<category><![CDATA[Project]]></category>
		<category><![CDATA[project open]]></category>
		<guid isPermaLink="false">https://dcn.nat.fau.eu/?p=24529</guid>

					<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>
		
		
		
			</item>
		<item>
		<title>In honor of Enrique Zuazua&#8217;s 60th. Birthday</title>
		<link>https://dcn.nat.fau.eu/in-honor-of-enrique-zuazuas-60th-birthday/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Tue, 28 Sep 2021 15:09:08 +0000</pubDate>
				<category><![CDATA[2021-resources]]></category>
		<category><![CDATA[All]]></category>
		<category><![CDATA[EZuazua]]></category>
		<category><![CDATA[EZuazua Events]]></category>
		<category><![CDATA[Resources]]></category>
		<category><![CDATA[E. Zuazua]]></category>
		<category><![CDATA[Enrique Zuazua]]></category>
		<category><![CDATA[Enrique Zuazua 60th Birthday]]></category>
		<category><![CDATA[Enrique Zuazua Iriondo]]></category>
		<guid isPermaLink="false">https://dcn.nat.fau.eu/?p=9888</guid>

					<description><![CDATA[Date: September 28th, 2021 Title: In honor of Enrique Zuazua&#8217;s 60th. Birthday In honor of Enrique Zuazua&#8216;s 60th. Birthday: -Enrique Zuazua&#8217;s 60th. Birthday meeting at FAU (Sep, 2021) -Listen &#8220;A Ragtime&#8220;, by Martin Gugat who delighted us with his beautiful composition during our Enrique Zuazua&#8217;s 60th. Birthday meet-up! &#8211;Words by Prof. Günter Leugering, FAU Senior [&#8230;]]]></description>
		
		
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			</item>
		<item>
		<title>Summer short course (China) 4/4: Control, Machine Learning and Numerics by E. Zuazua</title>
		<link>https://dcn.nat.fau.eu/summer-short-course-china-4-4-control-machine-learning-and-numerics-by-e-zuazua/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Mon, 26 Jul 2021 16:31:17 +0000</pubDate>
				<category><![CDATA[2021-resources]]></category>
		<category><![CDATA[All]]></category>
		<category><![CDATA[Course]]></category>
		<category><![CDATA[EZuazua]]></category>
		<category><![CDATA[EZuazua Akademy]]></category>
		<category><![CDATA[EZuazua Events]]></category>
		<category><![CDATA[Resources]]></category>
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					<description><![CDATA[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 [&#8230;]]]></description>
		
		
		
			</item>
		<item>
		<title>PhD Thesis defense: Nodal Control and Probabilistic Constrained Optimization using the Example of Gas Networks by Michael Schuster</title>
		<link>https://dcn.nat.fau.eu/phd-thesis-defense-nodal-control-and-probabilistic-constrained-optimization-using-the-example-of-gas-networks-by-michael-schuster/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Fri, 23 Jul 2021 18:05:06 +0000</pubDate>
				<category><![CDATA[2021-resources]]></category>
		<category><![CDATA[All]]></category>
		<category><![CDATA[Resources]]></category>
		<category><![CDATA[Thesis]]></category>
		<guid isPermaLink="false">https://dcn.nat.fau.eu/?p=8533</guid>

					<description><![CDATA[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 &#8211; Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg (Germany) On July 23rd, our team member Michael Schuster defended his PhD Thesis [&#8230;]]]></description>
		
		
		
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