Model Reduction and Surrogate Modeling (MORE)

Mon. 19

Tue. 20

Wed. 21

Thu. 22

Fri. 23

08:00

09:00

10:00

11:00

12:00

13:00

14:00

15:00

16:00

17:00

18:00

19:00

20:00

21:00

22:00

23:00

Registration

12:45 - 13:30 (45min)

Registration

Welcome of participants (H 3005)

Opening

13:30 - 14:00 (30min)

Opening

H 1012

Plenary

14:00 - 14:45 (45min)

Plenary

H 1012

Chair: Mario Ohlberger

› Nonlinear balanced truncation: Scalable computation and manifold reduction - Boris Kramer, University of California, San Diego 14:00-14:45 (45min)

Session 1

14:50 - 16:05 (1h15)

Session 1

H 1012

Chair: Mario Ohlberger

› Probabilistic reduced basis method for parameter-dependent problems - Marie BILLAUD FRIESS, Laboratoire de Mathématiques Jean Leray 14:50-15:15 (25min)

› Stability Analysis of Reduced Basis Model Predictive Control for Parametrized Optimal Control Problems - Saskia Dietze, RWTH Aachen University 15:15-15:40 (25min)

› Solving parametric PDEs with an enhanced model reduction method based on Linear/Ridge expansions - Constantin Greif, Ulm University 15:40-16:05 (25min)

Coffee break

16:05 - 16:30 (25min)

Coffee break

H 3005/3006

Parallel Session 1a
Parallel Session 1b

16:30 - 17:45 (1h15)

Parallel Session 1a

H 1012

Chair: Volker Mehrmann

› 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 16:30-16:55 (25min)

› Data-driven model order reduction with the p-AAA algorithm - Linus Balicki, Department of Mathematics, Virginia Polytechnic Institute and State University 16:55-17:20 (25min)

› Data-driven reduced-order modeling of thermo-mechanical models of machine tools - Quirin Aumann, Chemnitz University of Technology / Technische Universität Chemnitz 17:20-17:45 (25min)

16:30 - 17:45 (1h15)

Parallel Session 1b

H 1058

Chair: Lihong Feng

› Stochastic reduced order models for Bayesian estimation problems in fluid mechanics - valentin resseguier, Optimisation des procédés en Agriculture, Agroalimentaire et Environnement, Lab SCALIAN 16:30-16:55 (25min)

› A Reduced Basis Ensemble Kalman Method - Francesco Attilio Bruno Silva, Eindhoven University of Technology 16:55-17:20 (25min)

› Adapting Reduced Models for Importance Sampling - Patrick Héas, Institut National de Recherche en Informatique et en Automatique 17:20-17:45 (25min)

Parallel Session 2a
Parallel Session 2b

17:45 - 19:00 (1h15)

Parallel Session 2a

H 1012

Chair: Volker Mehrmann

› Data-Driven Enhanced Model Reduction for Bifurcating Models in Computational Fluid Dynamics - Martin Hess, SISSA MathLab [Trieste] 17:45-18:10 (25min)

› Data driven reduced modelling of the Vlasov-Poisson equation - Guillaume Steimer, Inria Nancy - Grand Est, Institut de Recherche Mathématique Avancée 18:10-18:35 (25min)

17:45 - 19:00 (1h15)

Parallel Session 2b

H 1058

Chair: Lihong Feng

› Parametric dynamic mode decomposition for nonlinear parametric dynamical systems - Shuwen Sun, Max Planck Institute for Dynamics of Complex Technical Systems 17:45-18:10 (25min)

› 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 18:10-18:35 (25min)

› A greedy MOR method for the tracking of eigensolutions to parametric PDEs - Francesca Bonizzoni, Faculty of Mathematics, University of Augsburg 18:35-19:00 (25min)

Welcome Reception

19:30 - 21:30 (2h)

Welcome Reception

A Foyer

Plenary

8:30 - 9:15 (45min)

Plenary

H 1012

Chair: Peter Benner

› Randomization techniques for solving large scale linear algebra problems - Laura Grigori, INRIA Paris 08:30-09:15 (45min)

Session 2

9:20 - 10:35 (1h15)

Session 2

H 1012

Chair: Peter Benner

› 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 09:20-09:45 (25min)

› 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 09:45-10:10 (25min)

› Adaptive POD-DEIM correction for Turing pattern approximation in reaction-diffusion PDE systems - Angela Monti, Università del Salento 10:10-10:35 (25min)

Coffee break

10:35 - 11:00 (25min)

Coffee break

H 3005/3006

Parallel Session 3a
Parallel Session 3b

11:00 - 12:40 (1h40)

Parallel Session 3a

H 1012

Chair: Bernard Haasdonk

› 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 11:00-11:25 (25min)

› Model Reduction of Navier-Stokes Equations using the Loewner Framework - Matthias Heinkenschloss 11:25-11:50 (25min)

› 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 11:50-12:15 (25min)

› POD-Based Adaptive Model Reduction to Accelerate Computational Fluid Dynamics - Victor Zucatti, Matthew J. Zahr 12:15-12:40 (25min)

11:00 - 12:40 (1h40)

Parallel Session 3b

H 1058

Chair: Heike Faßbender

› 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 11:00-11:25 (25min)

› Deep-Reinforcement-Learning-informed Adaptive Refinement for High-order Discontinuous Galerkin Methods - Corbin Foucart, Massachusetts Institute of Technology 11:25-11:50 (25min)

› On error estimates for reduced models obtained by balanced truncation - Björn Liljegren-Sailer, Trier University 11:50-12:15 (25min)

› Automated model reduction for pharmacology models - Jorge Cisneros, University of Washington 12:15-12:40 (25min)

Lunch

12:40 - 14:00 (1h20)

Lunch

Session 3

14:00 - 15:15 (1h15)

Session 3

EW201

Chair: Michael Hinze

› 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 14:00-14:25 (25min)

› 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 14:25-14:50 (25min)

› Nonlinear manifold Reduced Order Models with Convolutional Autoencoders and Reduced Over-Collocation method - Francesco Romor, SISSA MathLab [Trieste] 14:50-15:15 (25min)

Plenary

15:20 - 16:05 (45min)

Plenary

EW201

Chair: Michael Hinze

› Learning to Forecast Dynamical Systems from Streaming Data - Rachel Ward, UT Austin 15:20-16:05 (45min)

Coffee break

16:05 - 16:30 (25min)

Coffee break

H 3005/3006

Parallel Session 4a
Parallel Session 4b

16:30 - 17:45 (1h15)

Parallel Session 4a

H 1012

Chair: Matthias Heinkenschloss

› 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] 16:30-16:55 (25min)

› Full Order Model and Reduced Order Model Consistency for Evolve-Filter-Relax Regularization - Maria Strazzullo, Department of Mathematical Sciences [Torino] 16:55-17:20 (25min)

› Hyper-reduction of geometrically parameterized nonlinear microstructures - Theron Guo, Eindhoven University of Technology 17:20-17:45 (25min)

16:30 - 17:45 (1h15)

Parallel Session 4b

H 1058

Chair: Axel Klawonn

› Two-Scale Reduction of LOD Multiscale Models - Stephan Rave, University of Münster 16:30-16:55 (25min)

› Adaptive Localized Reduced Basis Methods in Multiscale PDE-Constrained Parameter Optimization - Tim Keil, Mathematics Münster, University of Münster 16:55-17:20 (25min)

› Model reduction of convection-dominated partial differential equations via optimization-based implicit feature tracking - Matthew Zahr, University of Notre Dame 17:20-17:45 (25min)

Plenary

8:30 - 9:15 (45min)

Plenary

H 1012

Chair: Gianluigi Rozza

› Simulation-based Bayesian inference and surrogate modeling - Youssef Marzouk, Massachusetts Institute of Technology 08:30-09:15 (45min)

Session 4

9:20 - 10:35 (1h15)

Session 4

H 1012

Chair: Gianluigi Rozza

› Deep learning and the dynamical low-rank approximation - Aaron Charous, Massachusetts Institute Of Technology 09:20-09:45 (25min)

› Generalized Neural Closure Models with Interpretability - Abhinav Gupta, Department of Mechanical Engineering [Massachusetts Institute of Technology] 09:45-10:10 (25min)

› Conditional gradient-based Identification of Non-linear Dynamics - Martin Weiser, Zuse Institute Berlin 10:10-10:35 (25min)

Coffee break

10:35 - 11:00 (25min)

Coffee break

H 3005/3006

Parallel Session 5a
Parallel Session 5b

11:00 - 12:40 (1h40)

Parallel Session 5a

H 1012

Chair: Anthony Nouy

› Symplectic Model Reduction of Hamiltonian Systems on Nonlinear Manifolds - Silke Glas, University of Twente 11:00-11:25 (25min)

› Model reduction for port-Hamiltonian descriptor systems - Volker Mehrmann, Technische Universität Berlin 11:25-11:50 (25min)

› Dynamic Mode Decomposition for Continuous Port-Hamiltonian Systems - Jonas Nicodemus, Stuttgart Center for Simulation Science (SC SimTech), University of Stuttgart 11:50-12:15 (25min)

› 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 12:15-12:40 (25min)

11:00 - 12:40 (1h40)

Parallel Session 5b

H 1058

Chair: Boris Kramer

› Model reduction of descriptor systems with quadratic output functional - Jennifer Przybilla, Max Planck Institute for Dynamics of Complex Technical Systems 11:00-11:25 (25min)

› Learning Quadratic Embeddings for Nonlinear Dynamical Systems using Deep Learning - Pawan Goyal, Max Planck Institute for Dynamics of Complex Technical Systems 11:25-11:50 (25min)

› Impact of the Convergence of Series Expansions on Model Reduction of Quadratic-Bilinear Systems - Alejandro Diaz, Rice University 11:50-12:15 (25min)

› Data-Driven Model Reduction for Gas Network Digital Twins - Christian Himpe, University of Munster 12:15-12:40 (25min)

Lunch

12:40 - 14:00 (1h20)

Lunch

Plenary

14:00 - 14:45 (45min)

Plenary

H 1012

Chair: Tobias Breiten

› Structure-preserving and adaptive reduced order models of conservative dynamical systems - Cecilia Pagliantini, TU/e Eindhoven 14:00-14:45 (45min)

Poster Blitz

15:00 - 16:30 (1h30)

Poster Blitz

H 1012

Chair: Tobias Breiten

› Neural Closure Model for Dynamic Mode Decomposition Forecasts - Tony Ryu, Massachusetts Institute of Technology 15:02-15:04 (02min)

› A Differential Geometric Formulation for Model Order Reduction on Manifolds - Patrick Buchfink, University of Stuttgart 15:04-15:06 (02min)

› A machine learning-based reduced order model for the investigation of the haemodynamics in coronary artery bypass grafts - Pierfrancesco Siena, SISSA 15:06-15:08 (02min)

› Adaptive Gaussian Process Regression for Efficient Building of Surrogate Models in Inverse Problems - Phillip Semler, Zuse Institut Berlin 15:08-15:10 (02min)

› An efficient computational framework for atmospheric and ocean flows - Michele Girfoglio, Scuola Internazionale Superiore di Studi Avanzati / International School for Advanced Studies 15:10-15:12 (02min)

› Analysis of Hyper Reduction for the Computation of Nonlinear Normal Modes - Lukas Bürger, KULeuven 15:12-15:14 (02min)

› 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 15:14-15:16 (02min)

› 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 15:16-15:18 (02min)

› Combining adaptive model order reduction and stochastic collocation for uncertainty quantification of vibroacoustic systems - Ulrich Römer, Institut für Dynamik und Schwingungen, Technische Universität Braunschweig 15:18-15:20 (02min)

› Data enhanced reduced order methods for turbulent flows - Anna Ivagnes, SISSA MathLab [Trieste] 15:20-15:22 (02min)

› Data-driven approaches for system identication and reduction - Dimitrios Karachalios, Max Planck Institute for Dynamics of Complex Technical Systems 15:22-15:24 (02min)

› Data-Driven Linearization of Nonlinear Finite Element Analyses - Giovanni Conni, Department of Mechanical Engineering [Leuven], Department of Computer Science [Leuven] 15:24-15:26 (02min)

› Dictionary-based Online-adaptive Structure-preserving Model Order Reduction for Parametric Hamiltonian Systems - Robin Herkert, University of Stuttgart 15:26-15:28 (02min)

› 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 15:28-15:30 (02min)

› Effective A-posteriori Error Estimation for Port-Hamiltonian Systems - Johannes Rettberg, University of Stuttgart, Institute of Engineering and Computational Mechanics 15:30-15:32 (02min)

› Efficient Hyper-Reduction of contact problems treated by Lagrange multipliers. - Simon LE BERRE, Laboratoire de simulation du combustible, CEA/DES/IRESNE/DEC/SESC 15:32-15:34 (02min)

› Hermite kernel surrogates for the value function of high-dimensional nonlinear optimal control problems - Tobias Ehring, University of Stuttgart 15:34-15:36 (02min)

› Hybrid Projection Methods with Recycling for Inverse Problems - Jiahua Jiang, University of Birmingham 15:36-15:38 (02min)

› Interpolatory (P)MOR via low-rank (tensor) approximation in general linear matrix equations - Jens Saak, Max Planck Institute for Dynamics of Complex Technical Systems 15:38-15:40 (02min)

› Low-rank methods in large scale constrained optimization - Martin Stoll, TU Chemnitz 15:40-15:42 (02min)

› Low-rank Parareal: a low-rank parallel-in-time integrator - Benjamin Carrel, Department of Mathematics, University of Geneva 15:42-15:44 (02min)

› M-M.E.S.S. 3.0 - Introducing Krylov-based solvers - Jens Saak, Max Planck Institute for Dynamics of Complex Technical Systems 15:44-15:46 (02min)

› Machine learning-based reduced order modelling: Towards intelligent digital twins - George Drakoulas, FEAC Engineering P.C., Department of Mechanical Engineering & Aeronautics, University of Patras 15:46-15:48 (02min)

› Mass-conserving and energy-consistent ROMs for the incompressible Navier-Stokes equations with time-dependent boundary conditions - Henrik Rosenberger, Centrum Wiskunde & Informatica 15:48-15:50 (02min)

› Model order reduction for wave-type problems with band-limited outputs of interest - Muhammad Hamza Khalid, Department of Applied Mathematics, University of Twente 15:50-15:52 (02min)

› 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 15:52-15:54 (02min)

› Multi-fidelity Optimization of an Acoustic Metamaterial using Model Order Reduction and Machine Learning - Sebastian Schopper, Gerhard Müller 15:54-15:56 (02min)

› Non-intrusive adaptive surrogate modeling of parametric frequency-response problems - Davide Pradovera, Faculty of Mathematics, University of Vienna, CSQI, EPFL 15:56-15:58 (02min)

› On Balanced Truncation Error Bound and Sign Parameters - Sean Reiter, Department of Mathematics, Virginia Tech 15:58-16:00 (02min)

› On the use of exponential integrators for large-scale Hamiltonian systems - Michel-Niklas Senn, TU Braunschweig 16:00-16:02 (02min)

› Operator inference method for mechanical systems - Yevgeniya Filanova, Max-Planck-Institut für Dynamik Komplexer Technischer Systeme 16:02-16:04 (02min)

› 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 16:04-16:06 (02min)

› pyMOR - Model Order Reduction with Python - Stephan Rave, University of Münster 16:06-16:08 (02min)

› Reduced Basis Methods for Time-Harmonic Maxwell's Equations - Anna Sanfilippo, University of Trento 16:08-16:10 (02min)

› Reduced order models for efficient uncertainty quantification of wooden structures with inhomogeneous material properties - Catharina Czech, Technical University of Munich 16:10-16:12 (02min)

› Reduction of single phase flow models in porous media using a quantity of interest - Jana Tarhini, IFP Energies Nouvelles 16:12-16:14 (02min)

› ROM for Large-scale Modelling of Urban Air Pollution - Moaad Khamlich, SISSA Scuola Internazionale Superiore di Studi Avanzati 16:14-16:16 (02min)

› Spectral approximation of Lyapunov operator equations with applications in high dimensional non-linear feedback control - Bernhard Höveler, Technische Universität Berlin 16:16-16:18 (02min)

› Subspace-Distance-Enabled Active Learning for Parametric Model Order Reduction of Dynamical Systems - Harshit Kapadia, Max Planck Institute for Dynamics of Complex Technical Systems 16:18-16:20 (02min)

› Symplectic formulation of PGD reduced-order models for structural dynamics applications - Clement Vella, LaMcube 16:20-16:22 (02min)

› Tensor Galerkin Proper Orthogonal Decomposition for Uncertainty Quantification of PDEs with Random Parameters - Jan Heiland, Max Planck Institute for Dynamics of Complex Technical Systems 16:22-16:24 (02min)

› Time extrapolation technique applied to POD-based ROM - Pablo Solán-Fustero, University of Zaragoza 16:24-16:26 (02min)

› 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 16:26-16:28 (02min)

Coffee break

16:30 - 17:00 (30min)

Coffee break

H 3005/3006

Poster Session

17:00 - 18:00 (1h)

Poster Session

H 3006

Conference Dinner

19:30 - 23:30 (4h)

Conference Dinner

Wartehalle

Plenary

8:30 - 9:15 (45min)

Plenary

H 1012

Chair: Ralf Zimmermann

› Digital Twins through Reduced Order Models and Machine Learning - Jan S. Hesthaven, Ecole Polytechnique Fédérale de Lausanne 08:30-09:15 (45min)

Session 5

9:20 - 10:35 (1h15)

Session 5

H 1012

Chair: Ralf Zimmermann

› Optimization based model order reduction for stochastic systems - Melina Freitag, Institute of Mathematics 09:20-09:45 (25min)

› Balanced Truncation for Bayesian Inference - Elizabeth Qian, California Institute of Technology 09:45-10:10 (25min)

› Semi-supervised Invertible DeepONets for Bayesian Inverse Problems - Sebastian Kaltenbach, Technical University of Munich 10:10-10:35 (25min)

Coffee break

10:35 - 11:00 (25min)

Coffee break

H 3005/3006

Parallel Session 6a
Parallel Session 6b

11:00 - 12:40 (1h40)

Parallel Session 6a

H 1012

Chair: Tobias Breiten

› Structured barycentric forms and their application to iterative data-driven model reduction of second-order systems - Ion Victor Gosea, Max-Planck-Institute Magdeburg 11:00-11:25 (25min)

› Structured L2-Optimal Parametric Model Order Reduction - Petar Mlinarić, Virginia Tech 11:25-11:50 (25min)

› High Order Approximations of the Operator Lyapunov Equation Have Low Rank - Luka Grubisic, University of Zagreb, Faculty of Science 11:50-12:15 (25min)

› Long-time prediction of nonlinear parametrized dynamical systems by deep learning-based reduced order models - Stefania Fresca, Politecnico di Milano 12:15-12:40 (25min)

11:00 - 12:40 (1h40)

Parallel Session 6b

H 1058

Chair: Mario Ohlberger

› Hybrid fluid/particle methods for kinetic equations describing neutral particles in nuclear fusion plasma-edge modelling - Vince Maes, KU Leuven, Department of Computer Science 11:00-11:25 (25min)

› Model Order Reduction in Contour Integral Methods for parametric PDEs - Mattia Manucci, Gran Sasso Science Institute 11:25-11:50 (25min)

› Inf-Sup-Constant-Free Error Estimation for Linear Parametric Systems - Sridhar Chellappa, Max Planck Institute for Dynamics of Complex Technical Systems 11:50-12:15 (25min)

› Parametric reduced order modelling for transport dominated systems via shifted POD deep learning models - Shubhaditya Burela, Technical University of Berlin 12:15-12:40 (25min)

Lunch

12:40 - 14:00 (1h20)

Lunch

Plenary

14:00 - 14:45 (45min)

Plenary

H 1012

Chair: Serkan Gugercin

› Port-Hamiltonian systems -- from a general modelling wishlist to surrogate models with guarantees - Benjamin Unger, SC Sim Tech, University of Stuttgart 14:00-14:45 (45min)

Session 6

14:50 - 16:05 (1h15)

Session 6

H 1012

Chair: Serkan Gugercin

› Registration-based model reduction of parameterized PDEs with spatio-parameter adaptivity - tommaso taddei, Inria Bordeaux South-West 14:50-15:15 (25min)

› 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 15:15-15:40 (25min)

› Neural networks investigation of bifurcating phenomena in fluid-dynamics - Federico Pichi, EPFL, École Polytechnique Fédérale de Lausanne, MCSS, Route Cantonale, 1015, Lausanne, Switzerland. 15:40-16:05 (25min)

Coffee break

16:05 - 16:30 (25min)

Coffee break

H 3005/3006

Session 7

16:30 - 17:45 (1h15)

Session 7

H 1012

Chair: Benjamin Peherstorfer

› Deep Orthogonal Decomposition via Mesh-Informed Neural Networks for Reduced Order Modeling of parametrized PDEs - Nicola Franco, Modeling and Scientific Computing [Milano] 16:30-16:55 (25min)

› An adaptive hierarchy of certified machine learning and reduced basis surrogates for parametrized PDEs - Felix Schindler, Mathematics Münster, University of Münster 16:55-17:20 (25min)

› Multiscale modeling of heterogeneous structures based on a localized model order reduction approach - Philipp Diercks, Bundesanstalt für Materialforschung und -prüfung (BAM) 17:20-17:45 (25min)

Plenary

8:30 - 9:15 (45min)

Plenary

H 1012

Chair: Karsten Urban

› Deep learning for reduced order modeling - Andrea Manzoni, MOX - Department of Mathematics, Politecnico di Milano 08:30-09:15 (45min)

Session 8

9:20 - 10:35 (1h15)

Session 8

H 1012

Chair: Karsten Urban

› Generating reduced order models parallel in time via random sampling - Julia Schleuß, Faculty of Mathematics and Computer Science, University of Münster 09:20-09:45 (25min)

› The local sample complexity of non-linear least squares approximation - Philipp Trunschke, Nantes Université 09:45-10:10 (25min)

› Randomized local model order reduction for nonlinear PDEs - Kathrin Smetana, Stevens Institute of Technology 10:10-10:35 (25min)

Coffee break

10:35 - 11:00 (25min)

Coffee break

H 3005/3006

Session 9

11:00 - 11:50 (50min)

Session 9

H 1012

Chair: Sara Grundel

› 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 11:00-11:25 (25min)

› Slow collective dynamics via data-driven approximation of the Koopman generator - Feliks Nüske, Max Planck Institute for Dynamics of Complex Technical Systems 11:25-11:50 (25min)

Plenary

11:55 - 12:40 (45min)

Plenary

H 1012

Chair: Sara Grundel

› Structure-preserving reduced-order models for parametric cross-diffusion systems - Virginie Ehrlacher, CERMICS, Paris 11:55-12:40 (45min)

Closing

12:40 - 12:50 (10min)

Closing

H 1012