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	<description>FAU DCN-AvH. Chair for Dynamics, Control, Machine Learning and Numerics -Alexander von Humboldt Professorship</description>
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		<title>Quantitative rapid stabilization of some PDE models</title>
		<link>https://dcn.nat.fau.eu/quantitative-rapid-stabilization-of-some-pde-models/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Fri, 08 Jul 2022 12:38:38 +0000</pubDate>
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		<guid isPermaLink="false">https://dcn.nat.fau.eu/?p=20653</guid>

					<description><![CDATA[Date: Fri. July 08, 2022 Organized by: FAU DCN-AvH, Chair for Dynamics, Control and Numerics – Alexander von Humboldt Professorship at FAU Friedrich-Alexander-Universität Erlangen-Nürnberg (Germany) Title: Quantitative rapid stabilization of some PDE models Speaker: Prof. Dr. Shengquan Xiang Affiliation: Mathematical Institute for Data Science at Johns Hopkins University (USA) Abstract. Quantitative stabilization is an active [&#8230;]]]></description>
		
		
		
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		<title>Quasi-reversibility methods of optimal control for ill-posed final value diffusion equations</title>
		<link>https://dcn.nat.fau.eu/quasi-reversibility-methods-of-optimal-control-for-ill-posed-final-value-diffusion-equations/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Tue, 05 Jul 2022 18:43:57 +0000</pubDate>
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					<description><![CDATA[Date: Tue. July 05, 2022 Organized by: FAU DCN-AvH, Chair for Dynamics, Control and Numerics &#8211; Alexander von Humboldt Professorship Title: Quasi-reversibility methods of optimal control for ill-posed final value diffusion equations Speaker: Visitor scientist Prof. Dr. Mahamadi Warma Affiliation: George Mason University (USA) Abstract. We consider optimal control problems associated to generally non-well posed [&#8230;]]]></description>
		
		
		
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		<title>Physics-inspired equivariant machine learning</title>
		<link>https://dcn.nat.fau.eu/physics-inspired-equivariant-machine-learning/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Wed, 22 Jun 2022 09:37:14 +0000</pubDate>
				<category><![CDATA[2022-resources]]></category>
		<category><![CDATA[FAUDCNSeminar]]></category>
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		<guid isPermaLink="false">https://dcn.nat.fau.eu/?p=19961</guid>

					<description><![CDATA[Date: Wed. June 22, 2022 Organized by: FAU DCN-AvH, Chair for Dynamics, Control and Numerics – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg (Germany) Title: Physics-inspired equivariant machine learning Speaker: Prof. Dr. Soledad Villar Affiliation: Mathematical Institute for Data Science at Johns Hopkins University (USA) Abstract. There has been enormous progress in the last few [&#8230;]]]></description>
		
		
		
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		<title>Deep redatuming for PDE and inverse problems</title>
		<link>https://dcn.nat.fau.eu/deep-redatuming-for-pde-and-inverse-problems/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Fri, 10 Jun 2022 05:42:10 +0000</pubDate>
				<category><![CDATA[2022-resources]]></category>
		<category><![CDATA[FAUDCNSeminar]]></category>
		<category><![CDATA[Resources]]></category>
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		<guid isPermaLink="false">https://dcn.nat.fau.eu/?p=19615</guid>

					<description><![CDATA[Date: Fri. June 10, 2022 Organized by: FAU DCN-AvH, Chair for Dynamics, Control and Numerics – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg (Germany) Title: Deep redatuming for PDE and inverse problems Speaker: Prof. Dr. Laurent Demanet Affiliation: MIT &#8211; Massachusetts Institute of Technology (USA) Abstract. Neural networks have been leveraged in non-trivial ways in [&#8230;]]]></description>
		
		
		
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		<title>FAU DCN-AvH at #NdW22 Long Night of Sciences</title>
		<link>https://dcn.nat.fau.eu/fau-dcn-avh-at-ndw22-long-night-of-sciences/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Sat, 21 May 2022 21:09:05 +0000</pubDate>
				<category><![CDATA[2022-resources]]></category>
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		<category><![CDATA[FAUDCNAvHSeminar]]></category>
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					<description><![CDATA[Date: Sat. May 21, 2022 18:00H – 00:00H Title: #NdW22 Long Night of Sciences (Lange Nacht der Wissenschaft) On Saturday May 21th, 2022 the #NdW22 &#8220;Lange Nacht der Wissenschaften&#8221; (Long Night of Sciences) took place in Erlangen, Fürth, and Nürnberg and our FAU DCN-AvH, Chair for Dynamics, Control, and Numerics &#8211; Alexander von Humboldt Professorship [&#8230;]]]></description>
		
		
		
			</item>
		<item>
		<title>Optimal Control Design for Fluid Mixing: from Open-Loop to Closed-Loop</title>
		<link>https://dcn.nat.fau.eu/optimal-control-design-for-fluid-mixing-from-open-loop-to-closed-loop/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Thu, 19 May 2022 12:59:46 +0000</pubDate>
				<category><![CDATA[2022-resources]]></category>
		<category><![CDATA[FAUDCNSeminar]]></category>
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		<category><![CDATA[Talk]]></category>
		<category><![CDATA[FAUDCNAvHSeminar]]></category>
		<guid isPermaLink="false">https://dcn.nat.fau.eu/?p=18695</guid>

					<description><![CDATA[Date: Thu. May 19, 2022 Organized by: Durham University, Seminars in Mathematical Sciences Title: Optimal Control Design for Fluid Mixing: from Open-Loop to Closed-Loop Speaker: Visitor scientist Prof. Dr. Weiwei Hu Affiliation: University of Georgia (USA) Abstract. The question of what velocity fields effectively enhance or prevent transport and mixing, or steer a scalar field [&#8230;]]]></description>
		
		
		
			</item>
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		<title>Some observations on the turnpike property and optimal actuator design</title>
		<link>https://dcn.nat.fau.eu/some-observations-on-the-turnpike-property-and-optimal-actuator-design/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Wed, 11 May 2022 15:26:23 +0000</pubDate>
				<category><![CDATA[2022-resources]]></category>
		<category><![CDATA[FAUDCNSeminar]]></category>
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					<description><![CDATA[Date: Wed. May 11, 2022 Organized by: FAU DCN-AvH, Chair for Dynamics, Control and Numerics – Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg (Germany) Title: Some observations on the turnpike property and optimal actuator design Speaker: Dr. Borjan Geshkovski Affiliation: MIT &#8211; Massachusetts Institute of Technology (USA) Abstract. The turnpike property in optimal control and [&#8230;]]]></description>
		
		
		
			</item>
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		<title>Robust Protection against Uncertainties in Discrete-Continuous Optimization</title>
		<link>https://dcn.nat.fau.eu/robust-protection-against-uncertainties-in-discrete-continuous-optimization/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Fri, 29 Apr 2022 15:52:17 +0000</pubDate>
				<category><![CDATA[2022-resources]]></category>
		<category><![CDATA[FAUDCNSeminar]]></category>
		<category><![CDATA[Resources]]></category>
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		<guid isPermaLink="false">https://dcn.nat.fau.eu/?p=17692</guid>

					<description><![CDATA[Date: Fri. April 29, 2022 Organized by: FAU DCN-AvH, Chair for Dynamics, Control and Numerics &#8211; Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg (Germany) Title: Robust Protection against Uncertainties in Discrete-Continuous Optimization Speaker: Prof. Dr. Frauke Liers Affiliation: FAU MoD Research Center for Mathematics of Data. Department of Data Science (DDS) Professorship of Optimization under [&#8230;]]]></description>
		
		
		
			</item>
		<item>
		<title>Quantum algorithms for computing observables of nonlinear partial differential equations</title>
		<link>https://dcn.nat.fau.eu/quantum-algorithms-for-computing-observables-of-nonlinear-partial-differential-equations/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Fri, 01 Apr 2022 19:06:31 +0000</pubDate>
				<category><![CDATA[2022-resources]]></category>
		<category><![CDATA[FAUDCNSeminar]]></category>
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		<guid isPermaLink="false">https://dcn.nat.fau.eu/?p=16903</guid>

					<description><![CDATA[Date: Fri. April 1, 2022 Organized by: FAU DCN-AvH, Chair for Dynamics, Control and Numerics &#8211; Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg (Germany) Title: Quantum algorithms for computing observables of nonlinear partial differential equations Speaker: Prof. Dr. Shi Jin  Affiliation: Shanghai Jiao Tong University (China) Abstract. Nonlinear partial differential equations (PDEs) are crucial to [&#8230;]]]></description>
		
		
		
			</item>
		<item>
		<title>Numerical algorithms as a tool that binds science disciplines with particular emphasis on matrix algorithms</title>
		<link>https://dcn.nat.fau.eu/numerical-algorithms-as-a-tool-that-binds-science-disciplines-with-particular-emphasis-on-matrix-algorithms/</link>
		
		<dc:creator><![CDATA[darlis.dcn]]></dc:creator>
		<pubDate>Fri, 04 Mar 2022 19:35:14 +0000</pubDate>
				<category><![CDATA[2022-resources]]></category>
		<category><![CDATA[FAUDCNSeminar]]></category>
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		<category><![CDATA[FAUDCNAvHSeminar]]></category>
		<guid isPermaLink="false">https://dcn.nat.fau.eu/?p=15925</guid>

					<description><![CDATA[Date: Fri. March 4, 2022 Organized by: FAU DCN-AvH, Chair for Dynamics, Control and Numerics &#8211; Alexander von Humboldt Professorship at FAU Erlangen-Nürnberg (Germany) Title: Numerical algorithms as a tool that binds science disciplines with particular emphasis on matrix algorithms Speaker: Prof. Dr. Hab. Eng. Jerzy Respondek Affiliation: Department of Applied Informatics, Silesian University of [&#8230;]]]></description>
		
		
		
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