Program
Monday, September 19, 2022
| Time |
Event |
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12:45 - 13:30
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Registration - Welcome of participants (H 3005) |
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13:30 - 14:00
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Opening (H 1012) |
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14:00 - 14:45
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Plenary (H 1012) - Chair: Mario Ohlberger |
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14:00 - 14:45 |
› Nonlinear balanced truncation: Scalable computation and manifold reduction - Boris Kramer, University of California, San Diego |
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14:50 - 16:05
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Session 1 (H 1012) - Chair: Mario Ohlberger |
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14:50 - 15:15 |
› Probabilistic reduced basis method for parameter-dependent problems - Marie BILLAUD FRIESS, Laboratoire de Mathématiques Jean Leray |
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15:15 - 15:40 |
› Stability Analysis of Reduced Basis Model Predictive Control for Parametrized Optimal Control Problems - Saskia Dietze, RWTH Aachen University |
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15:40 - 16:05 |
› Solving parametric PDEs with an enhanced model reduction method based on Linear/Ridge expansions - Constantin Greif, Ulm University |
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16:05 - 16:30
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Coffee break (H 3005/3006) |
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16:30 - 17:45
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Parallel Session 1a (H 1012) - Chair: Volker Mehrmann |
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16:30 - 16:55 |
› Data-driven learning of coarse basis functions in adaptive FETI-DP - Axel Klawonn, Department of Mathematics and Computer Science, Center for Data and Simulation Science |
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16:55 - 17:20 |
› Data-driven model order reduction with the p-AAA algorithm - Linus Balicki, Department of Mathematics, Virginia Polytechnic Institute and State University |
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17:20 - 17:45 |
› Data-driven reduced-order modeling of thermo-mechanical models of machine tools - Quirin Aumann, Chemnitz University of Technology / Technische Universität Chemnitz |
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16:30 - 17:45
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Parallel Session 1b (H 1058) - Chair: Lihong Feng |
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16:30 - 16:55 |
› Stochastic reduced order models for Bayesian estimation problems in fluid mechanics - valentin resseguier, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement, Lab SCALIAN |
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16:55 - 17:20 |
› A Reduced Basis Ensemble Kalman Method - Francesco Attilio Bruno Silva, Eindhoven University of Technology |
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17:20 - 17:45 |
› Adapting Reduced Models for Importance Sampling - Patrick Héas, Institut National de Recherche en Informatique et en Automatique |
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17:45 - 19:00
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Parallel Session 2a (H 1012) - Chair: Volker Mehrmann |
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17:45 - 18:10 |
› Data-Driven Enhanced Model Reduction for Bifurcating Models in Computational Fluid Dynamics - Martin Hess, SISSA MathLab [Trieste] |
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18:10 - 18:35 |
› Data driven reduced modelling of the Vlasov-Poisson equation - Guillaume Steimer, Inria Nancy - Grand Est, Institut de Recherche Mathématique Avancée |
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17:45 - 19:00
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Parallel Session 2b (H 1058) - Chair: Lihong Feng |
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17:45 - 18:10 |
› Parametric dynamic mode decomposition for nonlinear parametric dynamical systems - Shuwen Sun, Max Planck Institute for Dynamics of Complex Technical Systems |
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18:10 - 18:35 |
› Dominant Subspaces of High-Fidelity Nonlinear Structured Parametric Dynamical Systems and Model Reduction - Igor Pontes Duff, Max Planck Institute for Dynamics of Complex Technical Systems |
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18:35 - 19:00 |
› A greedy MOR method for the tracking of eigensolutions to parametric PDEs - Francesca Bonizzoni, Faculty of Mathematics, University of Augsburg |
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19:30 - 21:30
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Welcome Reception (A Foyer) |
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Tuesday, September 20, 2022
| Time |
Event |
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08:30 - 09:15
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Plenary (H 1012) - Chair: Peter Benner |
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08:30 - 09:15 |
› Randomization techniques for solving large scale linear algebra problems - Laura Grigori, INRIA Paris |
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09:20 - 10:35
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Session 2 (H 1012) - Chair: Peter Benner |
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09:20 - 09:45 |
› Model order reduction for Friedrichs' systems: a bridge between elliptic and hyperbolic problems - Davide Torlo, Scuola Internazionale Superiore di Studi Avanzati / International School for Advanced Studies |
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09:45 - 10:10 |
› Nonlinear model order reduction for hyperbolic conservation laws by means of diffeomorphic transformations of space-time domains - Hendrik Kleikamp, Institute for Analysis and Numerics, University of Münster |
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10:10 - 10:35 |
› Adaptive POD-DEIM correction for Turing pattern approximation in reaction-diffusion PDE systems - Angela Monti, Università del Salento |
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10:35 - 11:00
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Coffee break (H 3005/3006) |
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11:00 - 12:40
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Parallel Session 3a (H 1012) - Chair: Bernard Haasdonk |
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11:00 - 11:25 |
› A structure-preserving DEIM formulation for non-linearly stable hROMs of the incompressible Navier-Stokes equations - Robin Klein, Process and Energy Laboratory [Delft], Centrum Wiskunde & Informatica |
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11:25 - 11:50 |
› Model Reduction of Navier-Stokes Equations using the Loewner Framework - Matthias Heinkenschloss |
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11:50 - 12:15 |
› Model order reduction for turbulent and compressible flows: hybrid approaches in physics and geometry parametrization - giovanni stabile, International School for Advanced Studies, mathematics area, mathLab |
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12:15 - 12:40 |
› POD-Based Adaptive Model Reduction to Accelerate Computational Fluid Dynamics - Victor Zucatti, Matthew J. Zahr |
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11:00 - 12:40
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Parallel Session 3b (H 1058) - Chair: Heike Faßbender |
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11:00 - 11:25 |
› Matrix-free Transfer Function Prediction using Model Reduction and Machine Learning - Lihong Feng, Max Planck Institute for Dynamics of Complex Technical Systems - Giulio Antonini, UAq EMC Laboratory, Department of Industrial and Information Engineering and Economics, University of L'Aquila |
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11:25 - 11:50 |
› Deep-Reinforcement-Learning-informed Adaptive Refinement for High-order Discontinuous Galerkin Methods - Corbin Foucart, Massachusetts Institute of Technology |
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11:50 - 12:15 |
› On error estimates for reduced models obtained by balanced truncation - Björn Liljegren-Sailer, Trier University |
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12:15 - 12:40 |
› Automated model reduction for pharmacology models - Jorge Cisneros, University of Washington |
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12:40 - 14:00
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Lunch |
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14:00 - 15:15
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Session 3 (EW201) - Chair: Michael Hinze |
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14:00 - 14:25 |
› Model reduction for dynamics on deformable complex surfaces - Shaimaa Monem Abdelhafez, Max Planck Institute for Dynamics of Complex Technical Systems - Peter Benner, Max Planck Institute for Dynamics of Complex Technical Systems |
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14:25 - 14:50 |
› Nonlinear Model Order Reduction for Three-dimensional Discretized FE Models using Graph Convolutional Autoencoders - Jörg Fehr, Institute of Engineering and Computational Mechanics, University of Stuttgart - Jonas Kneifl, Institute of Engineering and Computational Mechanics, University of Stuttgart |
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14:50 - 15:15 |
› Nonlinear manifold Reduced Order Models with Convolutional Autoencoders and Reduced Over-Collocation method - Francesco Romor, SISSA MathLab [Trieste] |
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15:20 - 16:05
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Plenary (EW201) - Chair: Michael Hinze |
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15:20 - 16:05 |
› Learning to Forecast Dynamical Systems from Streaming Data - Rachel Ward, UT Austin |
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16:05 - 16:30
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Coffee break (H 3005/3006) |
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16:30 - 17:45
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Parallel Session 4a (H 1012) - Chair: Matthias Heinkenschloss |
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16:30 - 16:55 |
› Non-intrusive multi-physics PGD-based reduced model for the modeling of power electronic modules - Louis Schuler, Laboratoire de Mécanique Paris-Saclay, Mitsubishi Electric R&D Centre Europe [France] |
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16:55 - 17:20 |
› Full Order Model and Reduced Order Model Consistency for Evolve-Filter-Relax Regularization - Maria Strazzullo, Department of Mathematical Sciences [Torino] |
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17:20 - 17:45 |
› Hyper-reduction of geometrically parameterized nonlinear microstructures - Theron Guo, Eindhoven University of Technology |
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16:30 - 17:45
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Parallel Session 4b (H 1058) - Chair: Axel Klawonn |
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16:30 - 16:55 |
› Two-Scale Reduction of LOD Multiscale Models - Stephan Rave, University of Münster |
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16:55 - 17:20 |
› Adaptive Localized Reduced Basis Methods in Multiscale PDE-Constrained Parameter Optimization - Tim Keil, Mathematics Münster, University of Münster |
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17:20 - 17:45 |
› Model reduction of convection-dominated partial differential equations via optimization-based implicit feature tracking - Matthew Zahr, University of Notre Dame |
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Wednesday, September 21, 2022
| Time |
Event |
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08:30 - 09:15
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Plenary (H 1012) - Chair: Gianluigi Rozza |
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08:30 - 09:15 |
› Simulation-based Bayesian inference and surrogate modeling - Youssef Marzouk, Massachusetts Institute of Technology |
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09:20 - 10:35
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Session 4 (H 1012) - Chair: Gianluigi Rozza |
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09:20 - 09:45 |
› Deep learning and the dynamical low-rank approximation - Aaron Charous, Massachusetts Institute Of Technology |
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09:45 - 10:10 |
› Generalized Neural Closure Models with Interpretability - Abhinav Gupta, Department of Mechanical Engineering [Massachusetts Institute of Technology] |
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10:10 - 10:35 |
› Conditional gradient-based Identification of Non-linear Dynamics - Martin Weiser, Zuse Institute Berlin |
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10:35 - 11:00
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Coffee break (H 3005/3006) |
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11:00 - 12:40
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Parallel Session 5a (H 1012) - Chair: Anthony Nouy |
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11:00 - 11:25 |
› Symplectic Model Reduction of Hamiltonian Systems on Nonlinear Manifolds - Silke Glas, University of Twente |
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11:25 - 11:50 |
› Model reduction for port-Hamiltonian descriptor systems - Volker Mehrmann, Technische Universität Berlin |
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11:50 - 12:15 |
› Dynamic Mode Decomposition for Continuous Port-Hamiltonian Systems - Jonas Nicodemus, Stuttgart Center for Simulation Science (SC SimTech), University of Stuttgart |
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12:15 - 12:40 |
› A non-intrusive algorithm for parameterized model order reduction of LTI systems with guaranteed dissipativity - Tommaso Bradde, Politecnico di Torino, Department of Electronics and Telecommunications |
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11:00 - 12:40
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Parallel Session 5b (H 1058) - Chair: Boris Kramer |
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11:00 - 11:25 |
› Model reduction of descriptor systems with quadratic output functional - Jennifer Przybilla, Max Planck Institute for Dynamics of Complex Technical Systems |
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11:25 - 11:50 |
› Learning Quadratic Embeddings for Nonlinear Dynamical Systems using Deep Learning - Pawan Goyal, Max Planck Institute for Dynamics of Complex Technical Systems |
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11:50 - 12:15 |
› Impact of the Convergence of Series Expansions on Model Reduction of Quadratic-Bilinear Systems - Alejandro Diaz, Rice University |
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12:15 - 12:40 |
› Data-Driven Model Reduction for Gas Network Digital Twins - Christian Himpe, University of Munster |
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12:40 - 14:00
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Lunch |
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14:00 - 14:45
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Plenary (H 1012) - Chair: Tobias Breiten |
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14:00 - 14:45 |
› Structure-preserving and adaptive reduced order models of conservative dynamical systems - Cecilia Pagliantini, TU/e Eindhoven |
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15:00 - 16:30
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Poster Blitz (H 1012) - Chair: Tobias Breiten |
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15:02 - 15:04 |
› Neural Closure Model for Dynamic Mode Decomposition Forecasts - Tony Ryu, Massachusetts Institute of Technology |
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15:04 - 15:06 |
› A Differential Geometric Formulation for Model Order Reduction on Manifolds - Patrick Buchfink, University of Stuttgart |
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15:06 - 15:08 |
› A machine learning-based reduced order model for the investigation of the haemodynamics in coronary artery bypass grafts - Pierfrancesco Siena, SISSA |
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15:08 - 15:10 |
› Adaptive Gaussian Process Regression for Efficient Building of Surrogate Models in Inverse Problems - Phillip Semler, Zuse Institut Berlin |
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15:10 - 15:12 |
› An efficient computational framework for atmospheric and ocean flows - Michele Girfoglio, Scuola Internazionale Superiore di Studi Avanzati / International School for Advanced Studies |
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15:12 - 15:14 |
› Analysis of Hyper Reduction for the Computation of Nonlinear Normal Modes - Lukas Bürger, KULeuven |
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15:14 - 15:16 |
› Balancing-related model reduction of large-scale sparse systems in MATLAB and Octave with the MORLAB toolbox - Steffen W. R. Werner, Courant Institute of Mathematical Sciences, New York University |
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15:16 - 15:18 |
› Bayesian multi-fidelity inverse analysis for computationally demanding models in high stochastic dimensions - Jonas Nitzler, Institute for Computational Mechanics, Professorship of Data-driven Materials Modeling, Technical University of Munich |
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15:18 - 15:20 |
› Combining adaptive model order reduction and stochastic collocation for uncertainty quantification of vibroacoustic systems - Ulrich Römer, Institut für Dynamik und Schwingungen, Technische Universität Braunschweig |
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15:20 - 15:22 |
› Data enhanced reduced order methods for turbulent flows - Anna Ivagnes, SISSA MathLab [Trieste] |
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15:22 - 15:24 |
› Data-driven approaches for system identication and reduction - Dimitrios Karachalios, Max Planck Institute for Dynamics of Complex Technical Systems |
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15:24 - 15:26 |
› Data-Driven Linearization of Nonlinear Finite Element Analyses - Giovanni Conni, Department of Mechanical Engineering [Leuven], Department of Computer Science [Leuven] |
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15:26 - 15:28 |
› Dictionary-based Online-adaptive Structure-preserving Model Order Reduction for Parametric Hamiltonian Systems - Robin Herkert, University of Stuttgart |
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15:28 - 15:30 |
› Dynamical low rank approximation and parametric reduced order models for shallow water moment equations - Julian Koellermeier, University of Groningen - Philipp Krah, Technical University of Berlin - Jonas Kusch, University of Innsbruck |
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15:30 - 15:32 |
› Effective A-posteriori Error Estimation for Port-Hamiltonian Systems - Johannes Rettberg, University of Stuttgart, Institute of Engineering and Computational Mechanics |
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15:32 - 15:34 |
› Efficient Hyper-Reduction of contact problems treated by Lagrange multipliers. - Simon LE BERRE, Laboratoire de simulation du combustible, CEA/DES/IRESNE/DEC/SESC |
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15:34 - 15:36 |
› Hermite kernel surrogates for the value function of high-dimensional nonlinear optimal control problems - Tobias Ehring, University of Stuttgart |
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15:36 - 15:38 |
› Hybrid Projection Methods with Recycling for Inverse Problems - Jiahua Jiang, University of Birmingham |
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15:38 - 15:40 |
› Interpolatory (P)MOR via low-rank (tensor) approximation in general linear matrix equations - Jens Saak, Max Planck Institute for Dynamics of Complex Technical Systems |
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15:40 - 15:42 |
› Low-rank methods in large scale constrained optimization - Martin Stoll, TU Chemnitz |
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15:42 - 15:44 |
› Low-rank Parareal: a low-rank parallel-in-time integrator - Benjamin Carrel, Department of Mathematics, University of Geneva |
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15:44 - 15:46 |
› M-M.E.S.S. 3.0 - Introducing Krylov-based solvers - Jens Saak, Max Planck Institute for Dynamics of Complex Technical Systems |
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15:46 - 15:48 |
› Machine learning-based reduced order modelling: Towards intelligent digital twins - George Drakoulas, FEAC Engineering P.C., Department of Mechanical Engineering & Aeronautics, University of Patras |
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15:48 - 15:50 |
› Mass-conserving and energy-consistent ROMs for the incompressible Navier-Stokes equations with time-dependent boundary conditions - Henrik Rosenberger, Centrum Wiskunde & Informatica |
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15:50 - 15:52 |
› Model order reduction for wave-type problems with band-limited outputs of interest - Muhammad Hamza Khalid, Department of Applied Mathematics, University of Twente |
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15:52 - 15:54 |
› Model order reduction via substructuring for a nonlinear, switched, differential-algebraic machine tool model - Julia Vettermann, Technische Universität Chemnitz, Research Group Mathematics in Industry and Technology |
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15:54 - 15:56 |
› Multi-fidelity Optimization of an Acoustic Metamaterial using Model Order Reduction and Machine Learning - Sebastian Schopper, Gerhard Müller |
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15:56 - 15:58 |
› Non-intrusive adaptive surrogate modeling of parametric frequency-response problems - Davide Pradovera, Faculty of Mathematics, University of Vienna, CSQI, EPFL |
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15:58 - 16:00 |
› On Balanced Truncation Error Bound and Sign Parameters - Sean Reiter, Department of Mathematics, Virginia Tech |
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16:00 - 16:02 |
› On the use of exponential integrators for large-scale Hamiltonian systems - Michel-Niklas Senn, TU Braunschweig |
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16:02 - 16:04 |
› Operator inference method for mechanical systems - Yevgeniya Filanova, Max-Planck-Institut für Dynamik Komplexer Technischer Systeme |
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16:04 - 16:06 |
› Parametric model order reduction approach for quasi-static non-linear mechanical problems using an industrial code: application to an elasto-plastic material - Eki Agouzal, Inria Bordeaux - Sud-Ouest, Team Memphis, Institut de Mathématiques de Bordeaux, EDF R&D |
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16:06 - 16:08 |
› pyMOR - Model Order Reduction with Python - Stephan Rave, University of Münster |
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16:08 - 16:10 |
› Reduced Basis Methods for Time-Harmonic Maxwell's Equations - Anna Sanfilippo, University of Trento |
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16:10 - 16:12 |
› Reduced order models for efficient uncertainty quantification of wooden structures with inhomogeneous material properties - Catharina Czech, Technical University of Munich |
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16:12 - 16:14 |
› Reduction of single phase flow models in porous media using a quantity of interest - Jana Tarhini, IFP Energies Nouvelles |
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16:14 - 16:16 |
› ROM for Large-scale Modelling of Urban Air Pollution - Moaad Khamlich, SISSA Scuola Internazionale Superiore di Studi Avanzati |
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16:16 - 16:18 |
› Spectral approximation of Lyapunov operator equations with applications in high dimensional non-linear feedback control - Bernhard Höveler, Technische Universität Berlin |
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16:18 - 16:20 |
› Subspace-Distance-Enabled Active Learning for Parametric Model Order Reduction of Dynamical Systems - Harshit Kapadia, Max Planck Institute for Dynamics of Complex Technical Systems |
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16:20 - 16:22 |
› Symplectic formulation of PGD reduced-order models for structural dynamics applications - Clement Vella, LaMcube |
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16:22 - 16:24 |
› Tensor Galerkin Proper Orthogonal Decomposition for Uncertainty Quantification of PDEs with Random Parameters - Jan Heiland, Max Planck Institute for Dynamics of Complex Technical Systems |
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16:24 - 16:26 |
› Time extrapolation technique applied to POD-based ROM - Pablo Solán-Fustero, University of Zaragoza |
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16:26 - 16:28 |
› Towards a Benchmark Framework for Model Order Reduction in the Mathematical Research Data Initiative (MaRDI) - Kathryn Lund, Max Planck Institute for Dynamics of Complex Technical Systems |
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16:30 - 17:00
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Coffee break (H 3005/3006) |
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17:00 - 18:00
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Poster Session (H 3006) |
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19:30 - 23:30
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Conference Dinner (Wartehalle) |
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Thursday, September 22, 2022
| Time |
Event |
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08:30 - 09:15
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Plenary (H 1012) - Chair: Ralf Zimmermann |
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08:30 - 09:15 |
› Digital Twins through Reduced Order Models and Machine Learning - Jan S. Hesthaven, Ecole Polytechnique Fédérale de Lausanne |
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09:20 - 10:35
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Session 5 (H 1012) - Chair: Ralf Zimmermann |
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09:20 - 09:45 |
› Optimization based model order reduction for stochastic systems - Melina Freitag, Institute of Mathematics |
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09:45 - 10:10 |
› Balanced Truncation for Bayesian Inference - Elizabeth Qian, California Institute of Technology |
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10:10 - 10:35 |
› Semi-supervised Invertible DeepONets for Bayesian Inverse Problems - Sebastian Kaltenbach, Technical University of Munich |
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10:35 - 11:00
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Coffee break (H 3005/3006) |
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11:00 - 12:40
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Parallel Session 6a (H 1012) - Chair: Tobias Breiten |
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11:00 - 11:25 |
› Structured barycentric forms and their application to iterative data-driven model reduction of second-order systems - Ion Victor Gosea, Max-Planck-Institute Magdeburg |
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11:25 - 11:50 |
› Structured L2-Optimal Parametric Model Order Reduction - Petar Mlinarić, Virginia Tech |
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11:50 - 12:15 |
› High Order Approximations of the Operator Lyapunov Equation Have Low Rank - Luka Grubisic, University of Zagreb, Faculty of Science |
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12:15 - 12:40 |
› Long-time prediction of nonlinear parametrized dynamical systems by deep learning-based reduced order models - Stefania Fresca, Politecnico di Milano |
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11:00 - 12:40
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Parallel Session 6b (H 1058) - Chair: Mario Ohlberger |
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11:00 - 11:25 |
› Hybrid fluid/particle methods for kinetic equations describing neutral particles in nuclear fusion plasma-edge modelling - Vince Maes, KU Leuven, Department of Computer Science |
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11:25 - 11:50 |
› Model Order Reduction in Contour Integral Methods for parametric PDEs - Mattia Manucci, Gran Sasso Science Institute |
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11:50 - 12:15 |
› Inf-Sup-Constant-Free Error Estimation for Linear Parametric Systems - Sridhar Chellappa, Max Planck Institute for Dynamics of Complex Technical Systems |
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12:15 - 12:40 |
› Parametric reduced order modelling for transport dominated systems via shifted POD deep learning models - Shubhaditya Burela, Technical University of Berlin |
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12:40 - 14:00
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Lunch |
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14:00 - 14:45
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Plenary (H 1012) - Chair: Serkan Gugercin |
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14:00 - 14:45 |
› Port-Hamiltonian systems -- from a general modelling wishlist to surrogate models with guarantees - Benjamin Unger, SC Sim Tech, University of Stuttgart |
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14:50 - 16:05
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Session 6 (H 1012) - Chair: Serkan Gugercin |
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14:50 - 15:15 |
› Registration-based model reduction of parameterized PDEs with spatio-parameter adaptivity - tommaso taddei, Inria Bordeaux South-West |
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15:15 - 15:40 |
› A certified wavelet-based physics-informed neural network for nonlinear model reduction of parameterized partial differential equations - Lewin Ernst, Institute for Numerical Mathematics, Ulm University |
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15:40 - 16:05 |
› Neural networks investigation of bifurcating phenomena in fluid-dynamics - Federico Pichi, EPFL, École Polytechnique Fédérale de Lausanne, MCSS, Route Cantonale, 1015, Lausanne, Switzerland. |
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16:05 - 16:30
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Coffee break (H 3005/3006) |
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16:30 - 17:45
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Session 7 (H 1012) - Chair: Benjamin Peherstorfer |
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16:30 - 16:55 |
› Deep Orthogonal Decomposition via Mesh-Informed Neural Networks for Reduced Order Modeling of parametrized PDEs - Nicola Franco, Modeling and Scientific Computing [Milano] |
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16:55 - 17:20 |
› An adaptive hierarchy of certified machine learning and reduced basis surrogates for parametrized PDEs - Felix Schindler, Mathematics Münster, University of Münster |
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17:20 - 17:45 |
› Multiscale modeling of heterogeneous structures based on a localized model order reduction approach - Philipp Diercks, Bundesanstalt für Materialforschung und -prüfung (BAM) |
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Friday, September 23, 2022
| Time |
Event |
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08:30 - 09:15
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Plenary (H 1012) - Chair: Karsten Urban |
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08:30 - 09:15 |
› Deep learning for reduced order modeling - Andrea Manzoni, MOX - Department of Mathematics, Politecnico di Milano |
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09:20 - 10:35
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Session 8 (H 1012) - Chair: Karsten Urban |
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09:20 - 09:45 |
› Generating reduced order models parallel in time via random sampling - Julia Schleuß, Faculty of Mathematics and Computer Science, University of Münster |
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09:45 - 10:10 |
› The local sample complexity of non-linear least squares approximation - Philipp Trunschke, Nantes Université |
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10:10 - 10:35 |
› Randomized local model order reduction for nonlinear PDEs - Kathrin Smetana, Stevens Institute of Technology |
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10:35 - 11:00
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Coffee break (H 3005/3006) |
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11:00 - 11:50
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Session 9 (H 1012) - Chair: Sara Grundel |
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11:00 - 11:25 |
› Context-aware learning of low-dimensional stabilizing controllers in the scarce data regime - Steffen W. R. Werner, Courant Institute of Mathematical Sciences, New York University |
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11:25 - 11:50 |
› Slow collective dynamics via data-driven approximation of the Koopman generator - Feliks Nüske, Max Planck Institute for Dynamics of Complex Technical Systems |
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11:55 - 12:40
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Plenary (H 1012) - Chair: Sara Grundel |
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11:55 - 12:40 |
› Structure-preserving reduced-order models for parametric cross-diffusion systems - Virginie Ehrlacher, CERMICS, Paris |
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12:40 - 12:50
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Closing (H 1012) |
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